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.gitattributes

@@ -33,3 +33,10 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+assets/figure1_source/fonts/Ubuntu-Bold.ttf filter=lfs diff=lfs merge=lfs -text
+assets/figure1_source/fonts/Ubuntu-Regular.ttf filter=lfs diff=lfs merge=lfs -text
+assets/figure1.png filter=lfs diff=lfs merge=lfs -text
+assets/fonts/Ubuntu-Bold.ttf filter=lfs diff=lfs merge=lfs -text
+assets/fonts/Ubuntu-Regular.ttf filter=lfs diff=lfs merge=lfs -text
+paper/DooABLe_ICML.pdf filter=lfs diff=lfs merge=lfs -text
+results/ablations/plots/benchmark.png filter=lfs diff=lfs merge=lfs -text

CITATION.cff

@@ -0,0 +1,9 @@
+cff-version: 1.2.0
+message: "Please cite the accompanying manuscript when using DooABLe."
+title: "DooABLe: Learning Target Distributions with Budgeted Executable Paths"
+type: software
+version: 0.1.0
+date-released: 2026-09-12
+authors:
+  - name: "DooABLe contributors"
+license: MIT

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 DooABLe contributors
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,3 +1,144 @@
 ---
-license: apache-2.0
+language: en
+license: mit
+tags:
+  - molecular-design
+  - generative-modeling
+  - gflownet
+  - pytorch
+  - chemistry
 ---
+
+# DooABLe
+
+![DooABLe formulation and executable generation](assets/figure1.png)
+
+**Learning Target Distributions with Budgeted Executable Paths**
+
+DooABLe learns a specified distribution over reachable outcomes together with cost-dependent execution paths. The implementation supports finite action graphs, bounded string editing, lattice navigation, and reaction-based molecular construction. Molecular generation begins with a supplied parent inventory and permits a chosen number of additional reactions.
+
+For outcome weights $r(y)>0$, path cost $C(\xi)$, and route temperature $\tau>0$,
+
+$$P^*(\xi)=\frac{r(y)}{\sum_{y'}r(y')}\frac{e^{-C(\xi)/\tau}}{\sum_{\xi':y(\xi')=y}e^{-C(\xi')/\tau}}.$$
+
+The first factor specifies outcome probability. The second distributes that probability among feasible routes to the outcome. Prefix free energies are fitted through a backward recursion, and the forward sampler is trained with trajectory balance.
+
+## Install
+
+Python 3.12 or newer is required. The executed checks used Python 3.12 and CPU PyTorch. The small examples run on a CPU and fit comfortably in a few GB of RAM.
+
+```bash
+python -m venv .venv
+source .venv/bin/activate
+python -m pip install --upgrade pip
+python -m pip install torch --index-url https://download.pytorch.org/whl/cpu
+python -m pip install -e '.[test]'
+```
+
+The exact versions used for validation are in [docs/environment.json](docs/environment.json). To reproduce those versions, install [requirements-validated.txt](requirements-validated.txt) after the CPU PyTorch installation.
+
+## Shortest example
+
+```bash
+dooable toy --output results/demo/graph.json
+dooable train --graph results/demo/graph.json --steps 1200 --output results/demo/model
+dooable sample --model results/demo/model --n 1000 --output results/demo/samples.jsonl
+```
+
+This example has two equally weighted outcomes and unequal route counts. Training writes the graph, model weights, optimizer state, and progress measurements. Each sample contains its outcome, edge sequence, action records, total cost, and log probability.
+
+The exact dynamic program uses the same graph format.
+
+```bash
+dooable exact --graph results/demo/graph.json --temperature 0.7 --output results/demo/exact
+dooable sample --model results/demo/exact --n 1000 --output results/demo/exact_samples.jsonl
+```
+
+## Public molecular workflow
+
+The included inventory has 12 named parent compounds, 13 reagents, and four directional amide/ester templates. A budget of two produces 168 distinct outcomes under the declared reaction rules and 750 Da product cap. These compounds provide a reproducible chemistry example. Enamine experiments use the supplied local catalog through the same adapter.
+
+```bash
+dooable build --parents data/examples/parents.csv --reagents data/examples/reagents.csv --reactions data/examples/reactions.json --budget 2 --output results/public/graph.json
+```
+
+The public property workflow downloads Caco-2 Wang data through Therapeutics Data Commons and BACE inhibition data from MoleculeNet. It canonicalizes structures, averages duplicate labels, creates scaffold-disjoint partitions, and fits Morgan-fingerprint extra-trees predictors. The saved predictor weights are included at `results/validation/property_models/`. Refit them with
+
+```bash
+dooable fit-properties --data data/downloads --output results/public/property_models --seed 0
+```
+
+Use the included weights for the following generation run.
+
+```bash
+dooable score --graph results/public/graph.json --models results/validation/property_models --output results/public/rewards.json
+dooable train --graph results/public/graph.json --rewards results/public/rewards.json --temperature 0.7 --steps 1200 --output results/public/model
+dooable sample --model results/public/model --n 1000 --output results/public/samples.jsonl
+dooable replay --samples results/public/samples.jsonl --budget 2
+python scripts/evaluate_candidates.py --samples results/public/samples.jsonl --scores results/public/rewards.csv --budget 2 --requested 1000 --oracle-calls 168 --method dooable --output results/public/evaluation.json
+```
+
+BACE scores are predicted pIC50 values. Caco-2 scores are predicted log10 permeability in cm/s. Reaction replay checks the recorded graph transformations. Laboratory reaction success and experimental property measurements require separate experiments.
+
+## Benchmarks and plots
+
+```bash
+python scripts/run_benchmarks.py --config configs/toy.yaml
+python scripts/run_benchmarks.py --config configs/grid.yaml
+python scripts/run_benchmarks.py --config configs/strings.yaml
+python scripts/run_benchmarks.py --config configs/chemistry_small.yaml
+python scripts/run_benchmarks.py --config configs/ablations.yaml
+python scripts/plot_results.py --run results/toy
+python scripts/plot_results.py --run results/chemistry_small
+python scripts/sweep_exact.py
+```
+
+The implemented comparisons include uniform executable sampling, reference-process reward tilting, trajectory balance with uniform backward probabilities, DooABLe, and the exact joint law. Ablations change route cost, terminal merging, backward normalization, and prefix-value estimation. Runs save configuration, per-seed metrics, summary CSVs, and checkpoints. Plotting writes vector PDFs, PNGs, and a LaTeX table from those measurements.
+
+Budget and property sweeps use
+
+```bash
+python scripts/run_molecular.py --config configs/molecular_public.yaml
+python scripts/sweep_preferences.py --graph results/validation/chemistry_graph.json --models results/validation/property_models
+```
+
+Add `--neural-steps 1200` to the preference sweep to train a forward policy for each setting. Consecutive settings reuse the preceding network weights.
+
+## Local catalogs and experiment scope
+
+Edit the input paths in [configs/enamine_local.yaml](configs/enamine_local.yaml), then run
+
+```bash
+python scripts/run_molecular.py --config configs/enamine_local.yaml
+```
+
+The catalog reader accepts CSV, TSV, and gzip files with `id,smiles` or native `Enamine_ID,SMILES` columns. Reaction templates specify a parent and one reagent. The inventory schema, budget conventions, and state features are documented in [docs/data.md](docs/data.md).
+
+The implementation materializes the reachable graph for the supplied inventory. Each training run has a fixed graph, reward specification, and route temperature. Graph expansion can dominate cost as catalogs and budgets grow. The default local-catalog configuration uses 100 input rows and fails explicitly if its graph-size cap is exceeded.
+
+The full LIT-PCBA docking study, licensed Enamine experiments, released molecular encoders, and third-party SynFlowNet/RxnFlow/CGFlow/SyntheMol comparisons remain to be executed. Their dependencies and manuscript mappings are listed in [docs/experiments.md](docs/experiments.md). The included validation measurements cover the public property predictors, small reaction inventory, and discrete systems.
+
+## Checkpoints and checks
+
+Resume an interrupted run with the same graph and settings. `--steps` specifies the total update count.
+
+```bash
+dooable train --graph results/demo/graph.json --steps 2000 --resume results/demo/model --output results/demo/model
+python -m pytest -q
+```
+
+Use `--initialize PATH` to reuse network weights for a new reward specification on the same graph. Exact probability checks, route replay, scaffold separation, checkpoint reload, and resumed training are covered by the tests. Completed runs and measured values appear in [docs/validation.md](docs/validation.md).
+
+| Directory | Contents |
+|---|---|
+| `src/dooable` | Graphs, dynamic programs, learning, chemistry, property models, metrics |
+| `configs` | Runnable experiment configurations |
+| `scripts` | Benchmarks, sweeps, evaluation, and plot export |
+| `results` | Executed measurements and small trained models |
+| `paper` | ICML manuscript source and required figure PDFs |
+| `assets` | Final Figure 1, editable source, and licensed Ubuntu fonts |
+| `bibliography` | Verified reference records and primary-source URLs |
+
+## Citation and licenses
+
+The manuscript is a research draft with unfilled main-benchmark tables. Citation metadata are provided in [CITATION.cff](CITATION.cff). The source code uses the MIT license. Ubuntu fonts retain the Ubuntu Font Licence. Dataset sources and third-party assets retain their upstream terms, listed in [docs/data.md](docs/data.md).

assets/figure1_source/README.md

@@ -0,0 +1,10 @@
+# Editable Figure 1
+
+Install RDKit and CairoSVG to regenerate the molecular structures. XeLaTeX compiles the overview with the included Ubuntu fonts and Computer Modern mathematics.
+
+```bash
+python make_molecules.py
+xelatex -interaction=nonstopmode -halt-on-error overview.tex
+```
+
+The palette uses light blue `#65AEDB`, dark blue `#326889`, and pale blue `#EAF5FC`.

assets/figure1_source/fonts/UFL.txt

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+-------------------------------
+UBUNTU FONT LICENCE Version 1.0
+-------------------------------
+
+PREAMBLE
+This licence allows the licensed fonts to be used, studied, modified and
+redistributed freely. The fonts, including any derivative works, can be
+bundled, embedded, and redistributed provided the terms of this licence
+are met. The fonts and derivatives, however, cannot be released under
+any other licence. The requirement for fonts to remain under this
+licence does not require any document created using the fonts or their
+derivatives to be published under this licence, as long as the primary
+purpose of the document is not to be a vehicle for the distribution of
+the fonts.
+
+DEFINITIONS
+"Font Software" refers to the set of files released by the Copyright
+Holder(s) under this licence and clearly marked as such. This may
+include source files, build scripts and documentation.
+
+"Original Version" refers to the collection of Font Software components
+as received under this licence.
+
+"Modified Version" refers to any derivative made by adding to, deleting,
+or substituting -- in part or in whole -- any of the components of the
+Original Version, by changing formats or by porting the Font Software to
+a new environment.
+
+"Copyright Holder(s)" refers to all individuals and companies who have a
+copyright ownership of the Font Software.
+
+"Substantially Changed" refers to Modified Versions which can be easily
+identified as dissimilar to the Font Software by users of the Font
+Software comparing the Original Version with the Modified Version.
+
+To "Propagate" a work means to do anything with it that, without
+permission, would make you directly or secondarily liable for
+infringement under applicable copyright law, except executing it on a
+computer or modifying a private copy. Propagation includes copying,
+distribution (with or without modification and with or without charging
+a redistribution fee), making available to the public, and in some
+countries other activities as well.
+
+PERMISSION & CONDITIONS
+This licence does not grant any rights under trademark law and all such
+rights are reserved.
+
+Permission is hereby granted, free of charge, to any person obtaining a
+copy of the Font Software, to propagate the Font Software, subject to
+the below conditions:
+
+1) Each copy of the Font Software must contain the above copyright
+notice and this licence. These can be included either as stand-alone
+text files, human-readable headers or in the appropriate machine-
+readable metadata fields within text or binary files as long as those
+fields can be easily viewed by the user.
+
+2) The font name complies with the following:
+(a) The Original Version must retain its name, unmodified.
+(b) Modified Versions which are Substantially Changed must be renamed to
+avoid use of the name of the Original Version or similar names entirely.
+(c) Modified Versions which are not Substantially Changed must be
+renamed to both (i) retain the name of the Original Version and (ii) add
+additional naming elements to distinguish the Modified Version from the
+Original Version. The name of such Modified Versions must be the name of
+the Original Version, with "derivative X" where X represents the name of
+the new work, appended to that name.
+
+3) The name(s) of the Copyright Holder(s) and any contributor to the
+Font Software shall not be used to promote, endorse or advertise any
+Modified Version, except (i) as required by this licence, (ii) to
+acknowledge the contribution(s) of the Copyright Holder(s) or (iii) with
+their explicit written permission.
+
+4) The Font Software, modified or unmodified, in part or in whole, must
+be distributed entirely under this licence, and must not be distributed
+under any other licence. The requirement for fonts to remain under this
+licence does not affect any document created using the Font Software,
+except any version of the Font Software extracted from a document
+created using the Font Software may only be distributed under this
+licence.
+
+TERMINATION
+This licence becomes null and void if any of the above conditions are
+not met.
+
+DISCLAIMER
+THE FONT SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
+EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO ANY WARRANTIES OF
+MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT OF
+COPYRIGHT, PATENT, TRADEMARK, OR OTHER RIGHT. IN NO EVENT SHALL THE
+COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
+INCLUDING ANY GENERAL, SPECIAL, INDIRECT, INCIDENTAL, OR CONSEQUENTIAL
+DAMAGES, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
+FROM, OUT OF THE USE OR INABILITY TO USE THE FONT SOFTWARE OR FROM OTHER
+DEALINGS IN THE FONT SOFTWARE.

assets/figure1_source/fonts/Ubuntu-Bold.ttf

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+oid sha256:679b5c1e09cab3156bb8ef529735f9382bf31ca7ac737382ab959297f8d82ad4
+size 331612

assets/figure1_source/fonts/Ubuntu-Regular.ttf

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assets/figure1_source/make_diagnostics.py

@@ -0,0 +1,25 @@
+"""Empty experimental axes. No simulated curves or invented measurements."""
+from pathlib import Path
+import matplotlib
+matplotlib.use('Agg')
+import matplotlib.pyplot as plt
+from matplotlib import font_manager
+root=Path(__file__).resolve().parent
+font_manager.fontManager.addfont(str(root/'fonts/Ubuntu-Regular.ttf'))
+plt.rcParams.update({'font.family':'Ubuntu','font.size':9,'mathtext.fontset':'cm','axes.spines.top':False,'axes.spines.right':False,'axes.labelcolor':'#243644','axes.edgecolor':'#91A3AF','xtick.color':'#526C7D','ytick.color':'#526C7D','pdf.fonttype':42})
+fig,axs=plt.subplots(3,1,figsize=(3.25,3.9))
+spec=[('Route multiplicity',r'$P(Y=y_1)$',[1,4,8,16],(0,1)),('Route temperature',r'$\mathbb{E}[C\mid Y]$',[.1,1,2],None),('Training steps','Endpoint TV',[0,1000,2000],(0,1))]
+for ax,(xl,yl,ticks,ylim) in zip(axs,spec):
+ ax.set_xlabel(xl);ax.set_ylabel(yl);ax.set_xticks(ticks)
+ if ylim:ax.set_ylim(*ylim)
+ else:ax.set_yticks([])
+fig.tight_layout(pad=.5,h_pad=1.0);fig.savefig(root/'diagnostics.pdf');fig.savefig(root/'diagnostics.png',dpi=200)
+
+fig,axs=plt.subplots(2,1,figsize=(3.25,2.8))
+axs[0].set(xlabel='Affinity utility',ylabel='Permeability utility',xlim=(0,1),ylim=(0,1))
+axs[1].set(xlabel='Parent compounds',ylabel='Time (s)',xscale='log',xlim=(100,10000))
+axs[1].set_xticks([100,1000,10000],['100','1,000','10,000'])
+axs[1].set_yticks([])
+fig.tight_layout(pad=.6,h_pad=1.0)
+fig.savefig(root/'preferences.pdf')
+fig.savefig(root/'preferences.png',dpi=200)

assets/figure1_source/make_molecules.py

@@ -0,0 +1,26 @@
+"""Render structures used in the overview from explicit SMILES."""
+from pathlib import Path
+from rdkit import Chem
+from rdkit.Chem.Draw import rdMolDraw2D
+import cairosvg
+HERE=Path(__file__).resolve().parent
+structures={
+    'parent_acid':'O=C(O)c1ccccc1',
+    'parent_amine':'Nc1ccccc1',
+    'parent_aminoacid':'Nc1ccc(C(=O)O)cc1',
+    'product':'CNC(=O)c1ccc(NC(C)=O)cc1',
+}
+for name,smiles in structures.items():
+    drawer=rdMolDraw2D.MolDraw2DSVG(420,180) if name == "product" else rdMolDraw2D.MolDraw2DSVG(240,140)
+    options=drawer.drawOptions()
+    options.useBWAtomPalette()
+    options.clearBackground=False
+    options.bondLineWidth=2
+    options.fixedBondLength=28
+    options.fixedFontSize=26 if name == "product" else 24
+    options.fontFile=str(HERE/'fonts/Ubuntu-Regular.ttf')
+    drawer.DrawMolecule(Chem.MolFromSmiles(smiles))
+    drawer.FinishDrawing()
+    svg=drawer.GetDrawingText()
+    (HERE/f'{name}.svg').write_text(svg)
+    cairosvg.svg2pdf(bytestring=svg.encode(),write_to=str(HERE/f'{name}.pdf'))

assets/figure1_source/overview.tex

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+\documentclass[tikz,border=4pt]{standalone}
+\usepackage[no-math]{fontspec}
+\setmainfont{Ubuntu}[Path=fonts/,UprightFont=Ubuntu-Regular.ttf,BoldFont=Ubuntu-Bold.ttf]
+\usepackage{amsmath,amssymb,graphicx}
+\usetikzlibrary{arrows.meta,calc,decorations.pathreplacing}
+\definecolor{accent}{HTML}{65AEDB}
+\definecolor{darkaccent}{HTML}{326889}
+\definecolor{pale}{HTML}{EAF5FC}
+\definecolor{ink}{HTML}{243644}
+\definecolor{gray}{HTML}{91A3AF}
+\tikzset{every node/.style={font=\fontsize{9}{11}\selectfont,text=ink},arr/.style={-{Latex[length=1.8mm]},line width=.85pt,draw=gray},ga/.style={-{Latex[length=2.5mm]},line width=1.6pt,draw=accent},state/.style={circle,draw=accent,fill=white,minimum size=5mm,inner sep=1pt,line width=.8pt}}
+\newcommand{\mol}[3]{\begin{scope}[shift={(#1,#2)},scale=#3]
+\draw[ink,line width=.8pt] (30:.3)--(90:.3)--(150:.3)--(210:.3)--(270:.3)--(330:.3)--cycle;
+\draw[ink,line width=.5pt] (90:.22)--(150:.22) (210:.22)--(270:.22) (330:.22)--(30:.22);
+\draw[ink,line width=.8pt] (30:.3)--(.5,.29)--(.7,.17);
+\end{scope}}
+\begin{document}
+\begin{tikzpicture}[x=1cm,y=1cm]
+\path[use as bounding box] (0,0) rectangle (17.6,6.65);
+\node[anchor=west,font=\bfseries,text=darkaccent] at (.25,6.25) {Parents, admissible actions, budget $B$, outcome weights $r_z$, route temperature $\tau$};
+\path[fill=accent!10] (.25,3.05) .. controls (-.05,5.8) and (2.45,5.9) .. (2.7,4.4) .. controls (3.1,2.7) and (.2,2.05) .. (.25,3.05);
+\node at (1.4,5.0) {\includegraphics[width=2.3cm]{parent_acid.pdf}};
+\node at (1.4,3.92) {\includegraphics[width=2.3cm]{parent_amine.pdf}};
+\node at (1.4,2.94) {\includegraphics[width=2.3cm]{parent_aminoacid.pdf}};
+\node at (1.45,2.42) {$x_0\in\mathcal C$};
+
+\node[state] (u1) at (3.6,4.85) {};
+\node[state] (u2) at (3.6,3.28) {};
+\node[state] (v1) at (5.16,5.03) {};
+\node[state] (v2) at (5.16,4.02) {};
+\node[state] (v3) at (5.16,2.93) {};
+\node[state,fill=pale] (t1) at (6.9,4.73) {$y_1$};
+\node[state,fill=pale] (t2) at (6.9,3.15) {$y_2$};
+\draw[arr] (2.27,4.8)--(u1);\draw[arr] (2.25,3.48)--(u2);
+\draw[arr] (u1)--(v1);\draw[arr] (u1)--(v2);\draw[arr] (u2)--(v2);\draw[arr] (u2)--(v3);
+\draw[arr] (v1)--(t1);\draw[arr] (v2)--(t1);\draw[arr] (v3)--(t2);
+\draw[ga] (u2)--(v2)--(t1);
+\node at (5.1,2.42) {$\sum_i b(a_i)\leq B$};
+
+\node at (10.1,5.42) {$v(s)=\log\!\sum_{e:u\to s}e^{v(u)-c(e)/\tau}$};
+\draw[ga] (11.8,4.51) .. controls (10.2,4.95) and (8.8,4.86) .. (7.5,4.44);
+\node at (10.02,4.0) {$q(e\mid s)\propto e^{v(u)-c(e)/\tau}$};
+\draw[arr] (7.5,3.31) .. controls (8.83,2.9) and (10.35,2.89) .. (11.8,3.28);
+\node at (10.15,2.52) {$\log Z+\log P_\theta=\log r_z+\log Q_\phi$};
+
+\path[fill=accent!10] (13.24,4.14) .. controls (13.05,5.5) and (16.72,5.75) .. (17.05,4.63) .. controls (17.48,3.15) and (13.51,3.22) .. (13.24,4.14);
+\node at (15.15,4.68) {\includegraphics[width=4.2cm]{product.pdf}};
+\node at (15.2,3.65) {Sampled $(y,\xi)\sim P_\theta$};
+\draw[ga] (12.3,3.24) .. controls (12.75,3.29) and (13.05,3.67) .. (13.32,3.84);
+\draw[accent,line width=1pt] (14.0,2.89)--(16.6,2.89);
+\foreach \x in {14.15,15.28,16.41}{\fill[accent] (\x,2.89) circle (.065);}
+\node at (15.28,2.42) {$x_0\xrightarrow{a_1}x_1\xrightarrow{a_2}y$};
+\path[fill=pale,rounded corners=3pt] (.18,.02) rectangle (17.38,2.0);
+\node[anchor=west,font=\bfseries,text=darkaccent] at (.51,1.57) {DooABLe};
+\node[font=\fontsize{11}{13}\selectfont] at (9.7,1.0)
+{$\displaystyle P^*(\xi)=\underbrace{\frac{r_z(y)}{\sum_{y'\in\mathcal Y_B}r_z(y')}}_{\text{outcome probability}}\ \underbrace{\frac{e^{-C(\xi)/\tau}}{\sum_{\xi':\,y(\xi')=y}e^{-C(\xi')/\tau}}}_{\text{conditional route probability}}$};
+\end{tikzpicture}
+\end{document}
+

assets/fonts/UFL.txt

@@ -0,0 +1,96 @@
+-------------------------------
+UBUNTU FONT LICENCE Version 1.0
+-------------------------------
+
+PREAMBLE
+This licence allows the licensed fonts to be used, studied, modified and
+redistributed freely. The fonts, including any derivative works, can be
+bundled, embedded, and redistributed provided the terms of this licence
+are met. The fonts and derivatives, however, cannot be released under
+any other licence. The requirement for fonts to remain under this
+licence does not require any document created using the fonts or their
+derivatives to be published under this licence, as long as the primary
+purpose of the document is not to be a vehicle for the distribution of
+the fonts.
+
+DEFINITIONS
+"Font Software" refers to the set of files released by the Copyright
+Holder(s) under this licence and clearly marked as such. This may
+include source files, build scripts and documentation.
+
+"Original Version" refers to the collection of Font Software components
+as received under this licence.
+
+"Modified Version" refers to any derivative made by adding to, deleting,
+or substituting -- in part or in whole -- any of the components of the
+Original Version, by changing formats or by porting the Font Software to
+a new environment.
+
+"Copyright Holder(s)" refers to all individuals and companies who have a
+copyright ownership of the Font Software.
+
+"Substantially Changed" refers to Modified Versions which can be easily
+identified as dissimilar to the Font Software by users of the Font
+Software comparing the Original Version with the Modified Version.
+
+To "Propagate" a work means to do anything with it that, without
+permission, would make you directly or secondarily liable for
+infringement under applicable copyright law, except executing it on a
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bibliography/verified_references.csv

@@ -0,0 +1,73 @@
+key,title,authors,year,venue,doi,publication_url,metadata_source,verified_date,verification
+albergo2025stochasticinterpolants,Stochastic Interpolants: A Unifying Framework for Flows and Diffusions,Michael Albergo and Nicholas M. Boffi and Eric Vanden-Eijnden,2025,Journal of Machine Learning Research,,http://jmlr.org/papers/v26/23-1605.html,https://www.jmlr.org/papers/v26/23-1605.bib,2026-09-12,Official publisher BibTeX imported.
+austin2021d3pm,Structured Denoising Diffusion Models in Discrete State-Spaces,"Austin, Jacob and Johnson, Daniel D. and Ho, Jonathan and Tarlow, Daniel and van den Berg, Rianne",2021,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2021/hash/958c530554f78bcd8e97125b70e6973d-Abstract.html,https://proceedings.neurips.cc/paper_files/paper/2021/hash/958c530554f78bcd8e97125b70e6973d-Abstract.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+backward,Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization,"Gritsaev, Timofei and Morozov, Nikita and Samsonov, Sergey and Tiapkin, Daniil",2025,International Conference on Learning Representations,,https://proceedings.iclr.cc/paper_files/paper/2025/hash/f3efbcfe76bed022a37c5aeb1daf2326-Abstract-Conference.html,https://proceedings.iclr.cc/paper_files/paper/2025/hash/f3efbcfe76bed022a37c5aeb1daf2326-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+boffi2025flowmapmatching,Flow map matching with stochastic interpolants: A mathematical framework for consistency models,Nicholas Matthew Boffi and Michael Samuel Albergo and Eric Vanden-Eijnden,2025,Transactions on Machine Learning Research,,https://openreview.net/forum?id=cqDH0e6ak2,https://jmlr.org/tmlr/papers/bib/cqDH0e6ak2.bib,2026-09-12,Official publisher BibTeX imported.
+boffi2025selfdistillation,How to build a consistency model: Learning flow maps via self-distillation,"Boffi, Nicholas and Albergo, Michael and Vanden-Eijnden, Eric",2025,Advances in Neural Information Processing Systems,10.52202/085713-1121,https://proceedings.neurips.cc/paper_files/paper/2025/hash/2ff3605c9e442d55156d99fe4f5f228d-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2025/hash/2ff3605c9e442d55156d99fe4f5f228d-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+caco2,ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting,"Wang, Ning-Ning and Dong, Jie and Deng, Yin-Hua and Zhu, Min-Feng and Wen, Ming and Yao, Zhi-Jiang and Lu, Ai-Ping and Wang, Jian-Bing and Cao, Dong-Sheng",2016,Journal of Chemical Information and Modeling,10.1021/acs.jcim.5b00642,https://doi.org/10.1021/acs.jcim.5b00642,https://api.crossref.org/works/10.1021/acs.jcim.5b00642,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+campbell2022continuoustimediscrete,A Continuous Time Framework for Discrete Denoising Models,"Campbell, Andrew and Benton, Joe and De Bortoli, Valentin and Rainforth, Thomas and Deligiannidis, George and Doucet, Arnaud",2022,Advances in Neural Information Processing Systems,10.52202/068431-2049,https://proceedings.neurips.cc/paper_files/paper/2022/hash/b5b528767aa35f5b1a60fe0aaeca0563-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2022/hash/b5b528767aa35f5b1a60fe0aaeca0563-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+campbell2024generativeflows,Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design,"Campbell, Andrew and Yim, Jason and Barzilay, Regina and Rainforth, Tom and Jaakkola, Tommi",2024,Proceedings of the 41st International Conference on Machine Learning,,https://proceedings.mlr.press/v235/campbell24a.html,https://proceedings.mlr.press/v235/campbell24a.html,2026-09-12,Official publisher BibTeX imported.
+cbas,Conditioning by adaptive sampling for robust design,"Brookes, David and Park, Hahnbeom and Listgarten, Jennifer",2019,Proceedings of the 36th International Conference on Machine Learning,,https://proceedings.mlr.press/v97/brookes19a.html,https://proceedings.mlr.press/v97/brookes19a.html,2026-09-12,Official publisher BibTeX imported.
+cgflow,Compositional Flows for 3{D} Molecule and Synthesis Pathway Co-design,"Shen, Tony and Seo, Seonghwan and Irwin, Ross and Didi, Kieran and Olsson, Simon and Kim, Woo Youn and Ester, Martin",2025,Proceedings of the 42nd International Conference on Machine Learning,,https://proceedings.mlr.press/v267/shen25b.html,https://proceedings.mlr.press/v267/shen25b.html,2026-09-12,Official publisher BibTeX imported.
+chembo,ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations,"Korovina, Ksenia and Xu, Sailun and Kandasamy, Kirthevasan and Neiswanger, Willie and Poczos, Barnabas and Schneider, Jeff and Xing, Eric",2020,Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics,,https://proceedings.mlr.press/v108/korovina20a.html,https://proceedings.mlr.press/v108/korovina20a.html,2026-09-12,Official publisher BibTeX imported.
+chen2018neuralode,Neural Ordinary Differential Equations,"Chen, Ricky T. Q. and Rubanova, Yulia and Bettencourt, Jesse and Duvenaud, David K",2018,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf,https://proceedings.neurips.cc/paper_files/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Bibtex.bib,2026-09-12,Official publisher BibTeX imported.
+coms,Conservative Objective Models for Effective Offline Model-Based Optimization,"Trabucco, Brandon and Kumar, Aviral and Geng, Xinyang and Levine, Sergey",2021,Proceedings of the 38th International Conference on Machine Learning,,https://proceedings.mlr.press/v139/trabucco21a.html,https://proceedings.mlr.press/v139/trabucco21a.html,2026-09-12,Official publisher BibTeX imported.
+designbench,Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization,"Trabucco, Brandon and Geng, Xinyang and Kumar, Aviral and Levine, Sergey",2022,Proceedings of the 39th International Conference on Machine Learning,,https://proceedings.mlr.press/v162/trabucco22a.html,https://proceedings.mlr.press/v162/trabucco22a.html,2026-09-12,Official publisher BibTeX imported.
+dsb,"Diffusion Schr\""odinger Bridge with Applications to Score-Based Generative Modeling","De Bortoli, Valentin and Thornton, James and Heng, Jeremy and Doucet, Arnaud",2021,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2021/hash/940392f5f32a7ade1cc201767cf83e31-Abstract.html,https://proceedings.neurips.cc/paper_files/paper/2021/hash/940392f5f32a7ade1cc201767cf83e31-Abstract.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+extratrees,Extremely randomized trees,"Geurts, Pierre and Ernst, Damien and Wehenkel, Louis",2006,Machine Learning,10.1007/s10994-006-6226-1,https://doi.org/10.1007/s10994-006-6226-1,https://api.crossref.org/works/10.1007/s10994-006-6226-1,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+frans2025shortcutmodels,One Step Diffusion via Shortcut Models,"Frans, Kevin and Hafner, Danijar and Levine, Sergey and Abbeel, Pieter",2025,International Conference on Learning Representations,,https://proceedings.iclr.cc/paper_files/paper/2025/hash/559a0998fab1d19b80e7e43a5852401c-Abstract-Conference.html,https://proceedings.iclr.cc/paper_files/paper/2025/hash/559a0998fab1d19b80e7e43a5852401c-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+gat2024discreteflowmatching,Discrete Flow Matching,"Gat, Itai and Remez, Tal and Shaul, Neta and Kreuk, Felix and Chen, Ricky T. Q. and Synnaeve, Gabriel and Adi, Yossi and Lipman, Yaron",2024,Advances in Neural Information Processing Systems,10.52202/079017-4239,https://proceedings.neurips.cc/paper_files/paper/2024/hash/f0d629a734b56a642701bba7bc8bb3ed-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2024/hash/f0d629a734b56a642701bba7bc8bb3ed-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+gcpn,Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation,"You, Jiaxuan and Liu, Bowen and Ying, Zhitao and Pande, Vijay and Leskovec, Jure",2018,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2018/file/d60678e8f2ba9c540798ebbde31177e8-Paper.pdf,https://proceedings.neurips.cc/paper_files/paper/2018/file/d60678e8f2ba9c540798ebbde31177e8-Bibtex.bib,2026-09-12,Official publisher BibTeX imported.
+geng2025meanflows,Mean Flows for One-step Generative Modeling,"Geng, Zhengyang and Deng, Mingyang and Bai, Xingjian and Kolter, Zico and He, Kaiming",2025,Advances in Neural Information Processing Systems,10.52202/085713-2534,https://proceedings.neurips.cc/paper_files/paper/2025/hash/6d13e085b79d454da5910e4ca82a3d9d-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2025/hash/6d13e085b79d454da5910e4ca82a3d9d-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+gfn,Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation,"Bengio, Emmanuel and Jain, Moksh and Korablyov, Maksym and Precup, Doina and Bengio, Yoshua",2021,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2021/hash/e614f646836aaed9f89ce58e837e2310-Abstract.html,https://proceedings.neurips.cc/paper_files/paper/2021/hash/e614f646836aaed9f89ce58e837e2310-Abstract.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+gfnfoundations,GFlowNet Foundations,Yoshua Bengio and Salem Lahlou and Tristan Deleu and Edward J. Hu and Mo Tiwari and Emmanuel Bengio,2023,Journal of Machine Learning Research,,http://jmlr.org/papers/v24/22-0364.html,https://jmlr.org/papers/v24/22-0364.bib,2026-09-12,Official publisher BibTeX imported.
+grammarvae,Grammar Variational Autoencoder,Matt J. Kusner and Brooks Paige and Jos{\'e} Miguel Hern{\'a}ndez-Lobato,2017,Proceedings of the 34th International Conference on Machine Learning,,https://proceedings.mlr.press/v70/kusner17a.html,https://proceedings.mlr.press/v70/kusner17a.html,2026-09-12,Official publisher BibTeX imported.
+guacamol,GuacaMol: Benchmarking Models for de Novo Molecular Design,"Brown, Nathan and Fiscato, Marco and Segler, Marwin H.S. and Vaucher, Alain C.",2019,Journal of Chemical Information and Modeling,10.1021/acs.jcim.8b00839,https://doi.org/10.1021/acs.jcim.8b00839,https://api.crossref.org/works/10.1021/acs.jcim.8b00839,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+ho2020ddpm,Denoising Diffusion Probabilistic Models,"Ho, Jonathan and Jain, Ajay and Abbeel, Pieter",2020,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2020/hash/4c5bcfec8584af0d967f1ab10179ca4b-Abstract.html,https://proceedings.neurips.cc/paper_files/paper/2020/hash/4c5bcfec8584af0d967f1ab10179ca4b-Abstract.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+holderrieth2025generatormatching,Generator Matching: Generative modeling with arbitrary Markov processes,"Holderrieth, Peter and Havasi, Marton and Yim, Jason and Shaul, Neta and Gat, Itai and Jaakkola, Tommi and Karrer, Brian and Chen, Ricky T. Q. and Lipman, Yaron",2025,International Conference on Learning Representations,,https://proceedings.iclr.cc/paper_files/paper/2025/hash/819aaee144cb40e887a4aa9e781b1547-Abstract-Conference.html,https://proceedings.iclr.cc/paper_files/paper/2025/hash/819aaee144cb40e887a4aa9e781b1547-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+holderrieth2026diamondmaps,Diamond Maps: Efficient Reward Alignment via Stochastic Flow Maps,Peter Holderrieth and Douglas Chen and Luca Eyring and Ishin Shah and Giri Anantharaman and Yutong He and Zeynep Akata and Tommi Jaakkola and Nicholas Boffi and Max Simchowitz,2026,International Conference on Machine Learning,,https://icml.cc/virtual/2026/poster/61156,https://icml.cc/virtual/2026/poster/61156,2026-09-12,"Title, author list, year, and acceptance checked against official conference program."
+holderrieth2026glass,GLASS Flows: Efficient Inference for Reward Alignment of Flow and Diffusion Models,"Holderrieth, Peter and Singer, Uriel and Jaakkola, Tommi and Chen, Ricky T. Q. and Lipman, Yaron and Karrer, Brian",2026,International Conference on Learning Representations,,https://proceedings.iclr.cc/paper_files/paper/2026/hash/ad6ac52e02e14e0f2ddc0d4587ab47f1-Abstract-Conference.html,https://proceedings.iclr.cc/paper_files/paper/2026/hash/ad6ac52e02e14e0f2ddc0d4587ab47f1-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+imf,"Diffusion Schr\""odinger Bridge Matching","Shi, Yuyang and De Bortoli, Valentin and Campbell, Andrew and Doucet, Arnaud",2023,Advances in Neural Information Processing Systems,10.52202/075280-2717,https://proceedings.neurips.cc/paper_files/paper/2023/hash/c428adf74782c2092d254329b6b02482-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2023/hash/c428adf74782c2092d254329b6b02482-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+jtvae,Junction Tree Variational Autoencoder for Molecular Graph Generation,"Jin, Wengong and Barzilay, Regina and Jaakkola, Tommi",2018,Proceedings of the 35th International Conference on Machine Learning,,https://proceedings.mlr.press/v80/jin18a.html,https://proceedings.mlr.press/v80/jin18a.html,2026-09-12,Official publisher BibTeX imported.
+kim2024ctm,Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion,"Kim, Dongjun and Lai, Chieh-Hsin and Liao, WeiHsiang and Murata, Naoki and Takida, Yuhta and Uesaka, Toshimitsu and He, Yutong and Mitsufuji, Yuki and Ermon, Stefano",2024,International Conference on Learning Representations,,https://proceedings.iclr.cc/paper_files/paper/2024/hash/c204d12afa0175285e5aac65188808b4-Abstract-Conference.html,https://proceedings.iclr.cc/paper_files/paper/2024/hash/c204d12afa0175285e5aac65188808b4-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+kiyohara2025neuralstochasticflows,Neural Stochastic Flows: Solver-Free Modelling and Inference for SDE Solutions,"Kiyohara, Naoki and Johns, Edward and Li, Yingzhen",2025,Advances in Neural Information Processing Systems,10.52202/085713-0571,https://proceedings.neurips.cc/paper_files/paper/2025/hash/18abbeef8cfe9203fdf9053c9c4fe191-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2025/hash/18abbeef8cfe9203fdf9053c9c4fe191-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+lipman2023flowmatching,Flow Matching for Generative Modeling,Yaron Lipman and Ricky T. Q. Chen and Heli Ben-Hamu and Maximilian Nickel and Matthew Le,2023,International Conference on Learning Representations,,https://iclr.cc/virtual/2023/poster/11309,https://iclr.cc/virtual/2023/poster/11309,2026-09-12,"Title, author list, year, and acceptance checked against official conference program."
+litpcba,LIT-PCBA: An Unbiased Data Set for Machine Learning and Virtual Screening,"Tran-Nguyen, Viet-Khoa and Jacquemard, C\'elien and Rognan, Didier",2020,Journal of Chemical Information and Modeling,10.1021/acs.jcim.0c00155,https://doi.org/10.1021/acs.jcim.0c00155,https://api.crossref.org/works/10.1021/acs.jcim.0c00155,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+liu2023rectifiedflow,Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow,Xingchao Liu and Chengyue Gong and Qiang Liu,2023,International Conference on Learning Representations,,https://iclr.cc/virtual/2023/poster/11266,https://iclr.cc/virtual/2023/poster/11266,2026-09-12,"Title, author list, year, and acceptance checked against official conference program."
+lou2024sedd,Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution,"Lou, Aaron and Meng, Chenlin and Ermon, Stefano",2024,Proceedings of the 41st International Conference on Machine Learning,,https://proceedings.mlr.press/v235/lou24a.html,https://proceedings.mlr.press/v235/lou24a.html,2026-09-12,Official publisher BibTeX imported.
+mccallum2026strongstochasticflowmaps,Strong Stochastic Flow Maps,"McCallum, Sam and Blasingame, Zander W. and Herschell, Timothy and Rindtorff, Niklas and Tong, Alexander and Foster, James",2026,ICML Workshop on Structured Probabilistic Inference and Generative Modeling,,https://openreview.net/forum?id=X0Bj1j4vbW,https://spigmworkshop2026.github.io/papers/,2026-09-12,Workshop acceptance verified on official program. Author metadata checked against arXiv 2606.01086. Workshop version cited.
+min,Model Inversion Networks for Model-Based Optimization,"Kumar, Aviral and Levine, Sergey",2020,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2020/hash/373e4c5d8edfa8b74fd4b6791d0cf6dc-Abstract.html,https://proceedings.neurips.cc/paper_files/paper/2020/hash/373e4c5d8edfa8b74fd4b6791d0cf6dc-Abstract.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+mmd,A Kernel Two-Sample Test,"Arthur Gretton and Karsten M. Borgwardt and Malte J. Rasch and Bernhard Sch{{\""o}}lkopf and Alexander Smola",2012,Journal of Machine Learning Research,,http://jmlr.org/papers/v13/gretton12a.html,https://www.jmlr.org/papers/v13/gretton12a.bib,2026-09-12,Official publisher BibTeX imported.
+mogfn,Multi-Objective {GF}low{N}ets,"Jain, Moksh and Raparthy, Sharath Chandra and Hern\'{a}ndez-Garc\'{\i}a, Alex and Rector-Brooks, Jarrid and Bengio, Yoshua and Miret, Santiago and Bengio, Emmanuel",2023,Proceedings of the 40th International Conference on Machine Learning,,https://proceedings.mlr.press/v202/jain23a.html,https://proceedings.mlr.press/v202/jain23a.html,2026-09-12,Official publisher BibTeX imported.
+moleculenet,MoleculeNet: a benchmark for molecular machine learning,"Wu, Zhenqin and Ramsundar, Bharath and Feinberg, Evan~N. and Gomes, Joseph and Geniesse, Caleb and Pappu, Aneesh S. and Leswing, Karl and Pande, Vijay",2018,Chemical Science,10.1039/c7sc02664a,https://doi.org/10.1039/c7sc02664a,https://api.crossref.org/works/10.1039/c7sc02664a,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+molopt,{M}ol{D}iff: Addressing the Atom-Bond Inconsistency Problem in 3{D} Molecule Diffusion Generation,"Peng, Xingang and Guan, Jiaqi and Liu, Qiang and Ma, Jianzhu",2023,Proceedings of the 40th International Conference on Machine Learning,,https://proceedings.mlr.press/v202/peng23b.html,https://proceedings.mlr.press/v202/peng23b.html,2026-09-12,Official publisher BibTeX imported.
+morgan,Extended-Connectivity Fingerprints,"Rogers, David and Hahn, Mathew",2010,Journal of Chemical Information and Modeling,10.1021/ci100050t,https://doi.org/10.1021/ci100050t,https://api.crossref.org/works/10.1021/ci100050t,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+moses,Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models,"Polykovskiy, Daniil and Zhebrak, Alexander and Sanchez-Lengeling, Benjamin and Golovanov, Sergey and Tatanov, Oktai and Belyaev, Stanislav and Kurbanov, Rauf and Artamonov, Aleksey and Aladinskiy, Vladimir and Veselov, Mark and Kadurin, Artur and Johansson, Simon and Chen, Hongming and Nikolenko, Sergey and Aspuru-Guzik, Al\'an and Zhavoronkov, Alex",2020,Frontiers in Pharmacology,10.3389/fphar.2020.565644,https://doi.org/10.3389/fphar.2020.565644,https://api.crossref.org/works/10.3389/fphar.2020.565644,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+pmo,Sample Efficiency Matters: A Benchmark for Practical Molecular Optimization,"Gao, Wenhao and Fu, Tianfan and Sun, Jimeng and Coley, Connor",2022,Advances in Neural Information Processing Systems,10.52202/068431-1551,https://proceedings.neurips.cc/paper_files/paper/2022/hash/8644353f7d307baaf29bc1e56fe8e0ec-Abstract-Datasets_and_Benchmarks.html,https://proceedings.neurips.cc/paper_files/paper/2022/hash/8644353f7d307baaf29bc1e56fe8e0ec-Abstract-Datasets_and_Benchmarks.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+potaptchik2026metaflowmaps,Meta Flow Maps enable scalable reward alignment,Peter Potaptchik and Adhi Saravanan and Abbas Mammadov and Alvaro Prat and Michael Albergo and Yee-Whye Teh,2026,International Conference on Machine Learning,,https://icml.cc/virtual/2026/poster/64766,https://icml.cc/virtual/2026/poster/64766,2026-09-12,"Title, author list, year, and acceptance checked against official conference program."
+qed,Quantifying the chemical beauty of drugs,"Bickerton, G. Richard and Paolini, Gaia V. and Besnard, J\'er\'emy and Muresan, Sorel and Hopkins, Andrew L.",2012,Nature Chemistry,10.1038/nchem.1243,https://doi.org/10.1038/nchem.1243,https://api.crossref.org/works/10.1038/nchem.1243,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+retrostar,Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search,"Chen, Binghong and Li, Chengtao and Dai, Hanjun and Song, Le",2020,Proceedings of the 37th International Conference on Machine Learning,,https://proceedings.mlr.press/v119/chen20k.html,https://proceedings.mlr.press/v119/chen20k.html,2026-09-12,Official publisher BibTeX imported.
+rff,Random Features for Large-Scale Kernel Machines,"Rahimi, Ali and Recht, Benjamin",2007,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2007/file/013a006f03dbc5392effeb8f18fda755-Paper.pdf,https://proceedings.neurips.cc/paper_files/paper/2007/file/013a006f03dbc5392effeb8f18fda755-Bibtex.bib,2026-09-12,Official publisher BibTeX imported.
+rxnflow,Generative Flows on Synthetic Pathway for Drug Design,"Seo, Seonghwan and Kim, Minsu and Shen, Tony and Ester, Martin and Park, Jinkyoo and Ahn, Sungsoo and Kim, Woo Youn",2025,International Conference on Learning Representations,,https://proceedings.iclr.cc/paper_files/paper/2025/hash/24d36eee157559e0d2549455fba28f6a-Abstract-Conference.html,https://proceedings.iclr.cc/paper_files/paper/2025/hash/24d36eee157559e0d2549455fba28f6a-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+sabour2025alignyourflow,Align Your Flow: Scaling Continuous-Time Flow Map Distillation,"Sabour, Amirmojtaba and Fidler, Sanja and Kreis, Karsten",2025,Advances in Neural Information Processing Systems,10.52202/085713-4900,https://proceedings.neurips.cc/paper_files/paper/2025/hash/d79ac139911df25d27f14bbf008deaee-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2025/hash/d79ac139911df25d27f14bbf008deaee-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+sac,Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor,"Haarnoja, Tuomas and Zhou, Aurick and Abbeel, Pieter and Levine, Sergey",2018,Proceedings of the 35th International Conference on Machine Learning,,https://proceedings.mlr.press/v80/haarnoja18b.html,https://proceedings.mlr.press/v80/haarnoja18b.html,2026-09-12,Official publisher BibTeX imported.
+sahoo2024mdlm,Simple and Effective Masked Diffusion Language Models,"Sahoo, Subham S. and Arriola, Marianne and Schiff, Yair and Gokaslan, Aaron and Marroquin, Edgar and Chiu, Justin T. and Rush, Alexander and Kuleshov, Volodymyr",2024,Advances in Neural Information Processing Systems,10.52202/079017-4135,https://proceedings.neurips.cc/paper_files/paper/2024/hash/eb0b13cc515724ab8015bc978fdde0ad-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2024/hash/eb0b13cc515724ab8015bc978fdde0ad-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+scaffolds,The Properties of Known Drugs. 1. Molecular Frameworks,"Bemis, Guy W. and Murcko, Mark A.",1996,Journal of Medicinal Chemistry,10.1021/jm9602928,https://doi.org/10.1021/jm9602928,https://api.crossref.org/works/10.1021/jm9602928,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+sf2m,"Simulation-Free {S}chr\""odinger Bridges via Score and Flow Matching","Tong, Alexander Y. and Malkin, Nikolay and Fatras, Kilian and Atanackovic, Lazar and Zhang, Yanlei and Huguet, Guillaume and Wolf, Guy and Bengio, Yoshua",2024,Proceedings of The 27th International Conference on Artificial Intelligence and Statistics,,https://proceedings.mlr.press/v238/tong24a.html,https://proceedings.mlr.press/v238/tong24a.html,2026-09-12,Official publisher BibTeX imported.
+shaul2025generaldiscretepaths,Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective,"Shaul, Neta and Gat, Itai and Havasi, Marton and Severo, Daniel and Sriram, Anuroop and Holderrieth, Peter and Karrer, Brian and Lipman, Yaron and Chen, Ricky T. Q.",2025,International Conference on Learning Representations,,https://proceedings.iclr.cc/paper_files/paper/2025/hash/29cd7f8331d13ede6dc6d6ef3dfacb70-Abstract-Conference.html,https://proceedings.iclr.cc/paper_files/paper/2025/hash/29cd7f8331d13ede6dc6d6ef3dfacb70-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+shi2024simplifiedmasked,Simplified and Generalized Masked Diffusion for Discrete Data,"Shi, Jiaxin and Han, Kehang and Wang, Zhe and Doucet, Arnaud and Titsias, Michalis",2024,Advances in Neural Information Processing Systems,10.52202/079017-3277,https://proceedings.neurips.cc/paper_files/paper/2024/hash/bad233b9849f019aead5e5cc60cef70f-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2024/hash/bad233b9849f019aead5e5cc60cef70f-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+sohldickstein2015nonequilibrium,Deep Unsupervised Learning using Nonequilibrium Thermodynamics,"Sohl-Dickstein, Jascha and Weiss, Eric and Maheswaranathan, Niru and Ganguli, Surya",2015,Proceedings of the 32nd International Conference on Machine Learning,,https://proceedings.mlr.press/v37/sohl-dickstein15.html,https://proceedings.mlr.press/v37/sohl-dickstein15.html,2026-09-12,Official publisher BibTeX imported.
+song2021scorebased,Score-Based Generative Modeling through Stochastic Differential Equations,Yang Song and Jascha Sohl-Dickstein and Durk Kingma and Abhishek Kumar and Stefano Ermon and Ben Poole,2021,International Conference on Learning Representations,,https://iclr.cc/virtual/2021/poster/3177,https://iclr.cc/virtual/2021/poster/3177,2026-09-12,"Title, author list, year, and acceptance checked against official conference program."
+song2023consistencymodels,Consistency Models,"Song, Yang and Dhariwal, Prafulla and Chen, Mark and Sutskever, Ilya",2023,Proceedings of the 40th International Conference on Machine Learning,,https://proceedings.mlr.press/v202/song23a.html,https://proceedings.mlr.press/v202/song23a.html,2026-09-12,Official publisher BibTeX imported.
+stark2024dirichletflow,{D}irichlet Flow Matching with Applications to {DNA} Sequence Design,"Stark, Hannes and Jing, Bowen and Wang, Chenyu and Corso, Gabriele and Berger, Bonnie and Barzilay, Regina and Jaakkola, Tommi",2024,Proceedings of the 41st International Conference on Machine Learning,,https://proceedings.mlr.press/v235/stark24b.html,https://proceedings.mlr.press/v235/stark24b.html,2026-09-12,Official publisher BibTeX imported.
+subtb,Learning {GF}low{N}ets From Partial Episodes For Improved Convergence And Stability,"Madan, Kanika and Rector-Brooks, Jarrid and Korablyov, Maksym and Bengio, Emmanuel and Jain, Moksh and Nica, Andrei Cristian and Bosc, Tom and Bengio, Yoshua and Malkin, Nikolay",2023,Proceedings of the 40th International Conference on Machine Learning,,https://proceedings.mlr.press/v202/madan23a.html,https://proceedings.mlr.press/v202/madan23a.html,2026-09-12,Official publisher BibTeX imported.
+synflownet,SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints,"Cretu, Miruna and Harris, Charles and Igashov, Ilia and Schneuing, Arne and Segler, Marwin and Correia, Bruno and Roy, Julien and Bengio, Emmanuel and Lio, Pietro",2025,International Conference on Learning Representations,,https://proceedings.iclr.cc/paper_files/paper/2025/hash/7495fa446f10e9edef6e47b2d327596e-Abstract-Conference.html,https://proceedings.iclr.cc/paper_files/paper/2025/hash/7495fa446f10e9edef6e47b2d327596e-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+synthemol,Generative AI for designing and validating easily synthesizable and structurally novel antibiotics,"Swanson, Kyle and Liu, Gary and Catacutan, Denise B. and Arnold, Autumn and Zou, James and Stokes, Jonathan M.",2024,Nature Machine Intelligence,10.1038/s42256-024-00809-7,https://doi.org/10.1038/s42256-024-00809-7,https://doi.org/10.1038/s42256-024-00809-7,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+synthesisdags,Barking up the right tree: an approach to search over molecule synthesis DAGs,"Bradshaw, John and Paige, Brooks and Kusner, Matt J. and Segler, Marwin and Hern\'andez-Lobato, Jos\'e Miguel",2020,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2020/hash/4cc05b35c2f937c5bd9e7d41d3686fff-Abstract.html,https://proceedings.neurips.cc/paper_files/paper/2020/hash/4cc05b35c2f937c5bd9e7d41d3686fff-Abstract.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+synthesizable,A Model to Search for Synthesizable Molecules,"Bradshaw, John and Paige, Brooks and Kusner, Matt J and Segler, Marwin and Hern\'{a}ndez-Lobato, Jos\'{e} Miguel",2019,Advances in Neural Information Processing Systems,,https://proceedings.neurips.cc/paper_files/paper/2019/file/46d0671dd4117ea366031f87f3aa0093-Paper.pdf,https://proceedings.neurips.cc/paper_files/paper/2019/hash/46d0671dd4117ea366031f87f3aa0093-Abstract.html,2026-09-12,Official publisher BibTeX imported.
+targetdiff,{D}ecomp{D}iff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design,"Guan, Jiaqi and Zhou, Xiangxin and Yang, Yuwei and Bao, Yu and Peng, Jian and Ma, Jianzhu and Liu, Qiang and Wang, Liang and Gu, Quanquan",2023,Proceedings of the 40th International Conference on Machine Learning,,https://proceedings.mlr.press/v202/guan23a.html,https://proceedings.mlr.press/v202/guan23a.html,2026-09-12,Official publisher BibTeX imported.
+tb,Trajectory balance: Improved credit assignment in GFlowNets,"Whitammer, Esmeralda S. and Jain, Moksh and Bengio, Emmanuel and Sun, Chen and Bengio, Yoshua",2022,Advances in Neural Information Processing Systems,10.52202/068431-0431,https://proceedings.neurips.cc/paper_files/paper/2022/hash/27b51baca8377a0cf109f6ecc15a0f70-Abstract-Conference.html,https://proceedings.neurips.cc/paper_files/paper/2022/hash/27b51baca8377a0cf109f6ecc15a0f70-Abstract-Conference.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+tdc,Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development,"Huang, Kexin and Fu, Tianfan and Gao, Wenhao and Zhao, Yue and Roohani, Yusuf and Leskovec, Jure and Coley, Connor and Xiao, Cao and Sun, Jimeng and Zitnik, Marinka",2021,NeurIPS Datasets and Benchmarks,,https://datasets-benchmarks-proceedings.neurips.cc/paper_files/paper/2021/hash/4c56ff4ce4aaf9573aa5dff913df997a-Abstract-round1.html,https://datasets-benchmarks-proceedings.neurips.cc/paper_files/paper/2021/hash/4c56ff4ce4aaf9573aa5dff913df997a-Abstract-round1.html,2026-09-12,Publisher citation metadata imported. Conference year used for proceedings.
+tong2024minibatchot,Improving and generalizing flow-based generative models with minibatch optimal transport,Alexander Tong and Kilian Fatras and Nikolay Malkin and Guillaume Huguet and Yanlei Zhang and Jarrid Rector-Brooks and Guy Wolf and Yoshua Bengio,2024,Transactions on Machine Learning Research,,https://openreview.net/forum?id=CD9Snc73AW,https://jmlr.org/tmlr/papers/bib/CD9Snc73AW.bib,2026-09-12,Official publisher BibTeX imported.
+vina,"AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading","Trott, Oleg and Olson, Arthur J.",2010,Journal of Computational Chemistry,10.1002/jcc.21334,https://doi.org/10.1002/jcc.21334,https://api.crossref.org/works/10.1002/jcc.21334,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.
+vinaupdate,"AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings","Eberhardt, Jerome and Santos-Martins, Diogo and Tillack, Andreas F. and Forli, Stefano",2021,Journal of Chemical Information and Modeling,10.1021/acs.jcim.1c00203,https://doi.org/10.1021/acs.jcim.1c00203,https://api.crossref.org/works/10.1021/acs.jcim.1c00203,2026-09-12,Publisher-deposited DOI metadata. Print year used when provided.

bibliography/verified_references.json

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+  {
+    "key": "albergo2025stochasticinterpolants",
+    "title": "Stochastic Interpolants: A Unifying Framework for Flows and Diffusions",
+    "authors": "Michael Albergo and Nicholas M. Boffi and Eric Vanden-Eijnden",
+    "year": "2025",
+    "venue": "Journal of Machine Learning Research",
+    "doi": "",
+    "publication_url": "http://jmlr.org/papers/v26/23-1605.html",
+    "metadata_source": "https://www.jmlr.org/papers/v26/23-1605.bib",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "austin2021d3pm",
+    "title": "Structured Denoising Diffusion Models in Discrete State-Spaces",
+    "authors": "Austin, Jacob and Johnson, Daniel D. and Ho, Jonathan and Tarlow, Daniel and van den Berg, Rianne",
+    "year": "2021",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2021/hash/958c530554f78bcd8e97125b70e6973d-Abstract.html",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2021/hash/958c530554f78bcd8e97125b70e6973d-Abstract.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "backward",
+    "title": "Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization",
+    "authors": "Gritsaev, Timofei and Morozov, Nikita and Samsonov, Sergey and Tiapkin, Daniil",
+    "year": "2025",
+    "venue": "International Conference on Learning Representations",
+    "doi": "",
+    "publication_url": "https://proceedings.iclr.cc/paper_files/paper/2025/hash/f3efbcfe76bed022a37c5aeb1daf2326-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.iclr.cc/paper_files/paper/2025/hash/f3efbcfe76bed022a37c5aeb1daf2326-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "boffi2025flowmapmatching",
+    "title": "Flow map matching with stochastic interpolants: A mathematical framework for consistency models",
+    "authors": "Nicholas Matthew Boffi and Michael Samuel Albergo and Eric Vanden-Eijnden",
+    "year": "2025",
+    "venue": "Transactions on Machine Learning Research",
+    "doi": "",
+    "publication_url": "https://openreview.net/forum?id=cqDH0e6ak2",
+    "metadata_source": "https://jmlr.org/tmlr/papers/bib/cqDH0e6ak2.bib",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "boffi2025selfdistillation",
+    "title": "How to build a consistency model: Learning flow maps via self-distillation",
+    "authors": "Boffi, Nicholas and Albergo, Michael and Vanden-Eijnden, Eric",
+    "year": "2025",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "10.52202/085713-1121",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2025/hash/2ff3605c9e442d55156d99fe4f5f228d-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2025/hash/2ff3605c9e442d55156d99fe4f5f228d-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "caco2",
+    "title": "ADME Properties Evaluation in Drug Discovery: Prediction of Caco-2 Cell Permeability Using a Combination of NSGA-II and Boosting",
+    "authors": "Wang, Ning-Ning and Dong, Jie and Deng, Yin-Hua and Zhu, Min-Feng and Wen, Ming and Yao, Zhi-Jiang and Lu, Ai-Ping and Wang, Jian-Bing and Cao, Dong-Sheng",
+    "year": "2016",
+    "venue": "Journal of Chemical Information and Modeling",
+    "doi": "10.1021/acs.jcim.5b00642",
+    "publication_url": "https://doi.org/10.1021/acs.jcim.5b00642",
+    "metadata_source": "https://api.crossref.org/works/10.1021/acs.jcim.5b00642",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher-deposited DOI metadata. Print year used when provided."
+  },
+  {
+    "key": "campbell2022continuoustimediscrete",
+    "title": "A Continuous Time Framework for Discrete Denoising Models",
+    "authors": "Campbell, Andrew and Benton, Joe and De Bortoli, Valentin and Rainforth, Thomas and Deligiannidis, George and Doucet, Arnaud",
+    "year": "2022",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "10.52202/068431-2049",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2022/hash/b5b528767aa35f5b1a60fe0aaeca0563-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2022/hash/b5b528767aa35f5b1a60fe0aaeca0563-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "campbell2024generativeflows",
+    "title": "Generative Flows on Discrete State-Spaces: Enabling Multimodal Flows with Applications to Protein Co-Design",
+    "authors": "Campbell, Andrew and Yim, Jason and Barzilay, Regina and Rainforth, Tom and Jaakkola, Tommi",
+    "year": "2024",
+    "venue": "Proceedings of the 41st International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v235/campbell24a.html",
+    "metadata_source": "https://proceedings.mlr.press/v235/campbell24a.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "cbas",
+    "title": "Conditioning by adaptive sampling for robust design",
+    "authors": "Brookes, David and Park, Hahnbeom and Listgarten, Jennifer",
+    "year": "2019",
+    "venue": "Proceedings of the 36th International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v97/brookes19a.html",
+    "metadata_source": "https://proceedings.mlr.press/v97/brookes19a.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "cgflow",
+    "title": "Compositional Flows for 3{D} Molecule and Synthesis Pathway Co-design",
+    "authors": "Shen, Tony and Seo, Seonghwan and Irwin, Ross and Didi, Kieran and Olsson, Simon and Kim, Woo Youn and Ester, Martin",
+    "year": "2025",
+    "venue": "Proceedings of the 42nd International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v267/shen25b.html",
+    "metadata_source": "https://proceedings.mlr.press/v267/shen25b.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "chembo",
+    "title": "ChemBO: Bayesian Optimization of Small Organic Molecules with Synthesizable Recommendations",
+    "authors": "Korovina, Ksenia and Xu, Sailun and Kandasamy, Kirthevasan and Neiswanger, Willie and Poczos, Barnabas and Schneider, Jeff and Xing, Eric",
+    "year": "2020",
+    "venue": "Proceedings of the Twenty Third International Conference on Artificial Intelligence and Statistics",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v108/korovina20a.html",
+    "metadata_source": "https://proceedings.mlr.press/v108/korovina20a.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "chen2018neuralode",
+    "title": "Neural Ordinary Differential Equations",
+    "authors": "Chen, Ricky T. Q. and Rubanova, Yulia and Bettencourt, Jesse and Duvenaud, David K",
+    "year": "2018",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Paper.pdf",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2018/file/69386f6bb1dfed68692a24c8686939b9-Bibtex.bib",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "coms",
+    "title": "Conservative Objective Models for Effective Offline Model-Based Optimization",
+    "authors": "Trabucco, Brandon and Kumar, Aviral and Geng, Xinyang and Levine, Sergey",
+    "year": "2021",
+    "venue": "Proceedings of the 38th International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v139/trabucco21a.html",
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+    "authors": "Peter Potaptchik and Adhi Saravanan and Abbas Mammadov and Alvaro Prat and Michael Albergo and Yee-Whye Teh",
+    "year": "2026",
+    "venue": "International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://icml.cc/virtual/2026/poster/64766",
+    "metadata_source": "https://icml.cc/virtual/2026/poster/64766",
+    "verified_date": "2026-09-12",
+    "verification": "Title, author list, year, and acceptance checked against official conference program."
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+  {
+    "key": "qed",
+    "title": "Quantifying the chemical beauty of drugs",
+    "authors": "Bickerton, G. Richard and Paolini, Gaia V. and Besnard, J\\'er\\'emy and Muresan, Sorel and Hopkins, Andrew L.",
+    "year": "2012",
+    "venue": "Nature Chemistry",
+    "doi": "10.1038/nchem.1243",
+    "publication_url": "https://doi.org/10.1038/nchem.1243",
+    "metadata_source": "https://api.crossref.org/works/10.1038/nchem.1243",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher-deposited DOI metadata. Print year used when provided."
+  },
+  {
+    "key": "retrostar",
+    "title": "Retro*: Learning Retrosynthetic Planning with Neural Guided A* Search",
+    "authors": "Chen, Binghong and Li, Chengtao and Dai, Hanjun and Song, Le",
+    "year": "2020",
+    "venue": "Proceedings of the 37th International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v119/chen20k.html",
+    "metadata_source": "https://proceedings.mlr.press/v119/chen20k.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "rff",
+    "title": "Random Features for Large-Scale Kernel Machines",
+    "authors": "Rahimi, Ali and Recht, Benjamin",
+    "year": "2007",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2007/file/013a006f03dbc5392effeb8f18fda755-Paper.pdf",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2007/file/013a006f03dbc5392effeb8f18fda755-Bibtex.bib",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
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+  {
+    "key": "rxnflow",
+    "title": "Generative Flows on Synthetic Pathway for Drug Design",
+    "authors": "Seo, Seonghwan and Kim, Minsu and Shen, Tony and Ester, Martin and Park, Jinkyoo and Ahn, Sungsoo and Kim, Woo Youn",
+    "year": "2025",
+    "venue": "International Conference on Learning Representations",
+    "doi": "",
+    "publication_url": "https://proceedings.iclr.cc/paper_files/paper/2025/hash/24d36eee157559e0d2549455fba28f6a-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.iclr.cc/paper_files/paper/2025/hash/24d36eee157559e0d2549455fba28f6a-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "sabour2025alignyourflow",
+    "title": "Align Your Flow: Scaling Continuous-Time Flow Map Distillation",
+    "authors": "Sabour, Amirmojtaba and Fidler, Sanja and Kreis, Karsten",
+    "year": "2025",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "10.52202/085713-4900",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2025/hash/d79ac139911df25d27f14bbf008deaee-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2025/hash/d79ac139911df25d27f14bbf008deaee-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "sac",
+    "title": "Soft Actor-Critic: Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor",
+    "authors": "Haarnoja, Tuomas and Zhou, Aurick and Abbeel, Pieter and Levine, Sergey",
+    "year": "2018",
+    "venue": "Proceedings of the 35th International Conference on Machine Learning",
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+    "publication_url": "https://proceedings.mlr.press/v80/haarnoja18b.html",
+    "metadata_source": "https://proceedings.mlr.press/v80/haarnoja18b.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "sahoo2024mdlm",
+    "title": "Simple and Effective Masked Diffusion Language Models",
+    "authors": "Sahoo, Subham S. and Arriola, Marianne and Schiff, Yair and Gokaslan, Aaron and Marroquin, Edgar and Chiu, Justin T. and Rush, Alexander and Kuleshov, Volodymyr",
+    "year": "2024",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "10.52202/079017-4135",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/eb0b13cc515724ab8015bc978fdde0ad-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/eb0b13cc515724ab8015bc978fdde0ad-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "scaffolds",
+    "title": "The Properties of Known Drugs. 1. Molecular Frameworks",
+    "authors": "Bemis, Guy W. and Murcko, Mark A.",
+    "year": "1996",
+    "venue": "Journal of Medicinal Chemistry",
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+    "publication_url": "https://doi.org/10.1021/jm9602928",
+    "metadata_source": "https://api.crossref.org/works/10.1021/jm9602928",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher-deposited DOI metadata. Print year used when provided."
+  },
+  {
+    "key": "sf2m",
+    "title": "Simulation-Free {S}chr\\\"odinger Bridges via Score and Flow Matching",
+    "authors": "Tong, Alexander Y. and Malkin, Nikolay and Fatras, Kilian and Atanackovic, Lazar and Zhang, Yanlei and Huguet, Guillaume and Wolf, Guy and Bengio, Yoshua",
+    "year": "2024",
+    "venue": "Proceedings of The 27th International Conference on Artificial Intelligence and Statistics",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v238/tong24a.html",
+    "metadata_source": "https://proceedings.mlr.press/v238/tong24a.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "shaul2025generaldiscretepaths",
+    "title": "Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective",
+    "authors": "Shaul, Neta and Gat, Itai and Havasi, Marton and Severo, Daniel and Sriram, Anuroop and Holderrieth, Peter and Karrer, Brian and Lipman, Yaron and Chen, Ricky T. Q.",
+    "year": "2025",
+    "venue": "International Conference on Learning Representations",
+    "doi": "",
+    "publication_url": "https://proceedings.iclr.cc/paper_files/paper/2025/hash/29cd7f8331d13ede6dc6d6ef3dfacb70-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.iclr.cc/paper_files/paper/2025/hash/29cd7f8331d13ede6dc6d6ef3dfacb70-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "shi2024simplifiedmasked",
+    "title": "Simplified and Generalized Masked Diffusion for Discrete Data",
+    "authors": "Shi, Jiaxin and Han, Kehang and Wang, Zhe and Doucet, Arnaud and Titsias, Michalis",
+    "year": "2024",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "10.52202/079017-3277",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/bad233b9849f019aead5e5cc60cef70f-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2024/hash/bad233b9849f019aead5e5cc60cef70f-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "sohldickstein2015nonequilibrium",
+    "title": "Deep Unsupervised Learning using Nonequilibrium Thermodynamics",
+    "authors": "Sohl-Dickstein, Jascha and Weiss, Eric and Maheswaranathan, Niru and Ganguli, Surya",
+    "year": "2015",
+    "venue": "Proceedings of the 32nd International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v37/sohl-dickstein15.html",
+    "metadata_source": "https://proceedings.mlr.press/v37/sohl-dickstein15.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "song2021scorebased",
+    "title": "Score-Based Generative Modeling through Stochastic Differential Equations",
+    "authors": "Yang Song and Jascha Sohl-Dickstein and Durk Kingma and Abhishek Kumar and Stefano Ermon and Ben Poole",
+    "year": "2021",
+    "venue": "International Conference on Learning Representations",
+    "doi": "",
+    "publication_url": "https://iclr.cc/virtual/2021/poster/3177",
+    "metadata_source": "https://iclr.cc/virtual/2021/poster/3177",
+    "verified_date": "2026-09-12",
+    "verification": "Title, author list, year, and acceptance checked against official conference program."
+  },
+  {
+    "key": "song2023consistencymodels",
+    "title": "Consistency Models",
+    "authors": "Song, Yang and Dhariwal, Prafulla and Chen, Mark and Sutskever, Ilya",
+    "year": "2023",
+    "venue": "Proceedings of the 40th International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v202/song23a.html",
+    "metadata_source": "https://proceedings.mlr.press/v202/song23a.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "stark2024dirichletflow",
+    "title": "{D}irichlet Flow Matching with Applications to {DNA} Sequence Design",
+    "authors": "Stark, Hannes and Jing, Bowen and Wang, Chenyu and Corso, Gabriele and Berger, Bonnie and Barzilay, Regina and Jaakkola, Tommi",
+    "year": "2024",
+    "venue": "Proceedings of the 41st International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v235/stark24b.html",
+    "metadata_source": "https://proceedings.mlr.press/v235/stark24b.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "subtb",
+    "title": "Learning {GF}low{N}ets From Partial Episodes For Improved Convergence And Stability",
+    "authors": "Madan, Kanika and Rector-Brooks, Jarrid and Korablyov, Maksym and Bengio, Emmanuel and Jain, Moksh and Nica, Andrei Cristian and Bosc, Tom and Bengio, Yoshua and Malkin, Nikolay",
+    "year": "2023",
+    "venue": "Proceedings of the 40th International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v202/madan23a.html",
+    "metadata_source": "https://proceedings.mlr.press/v202/madan23a.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "synflownet",
+    "title": "SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints",
+    "authors": "Cretu, Miruna and Harris, Charles and Igashov, Ilia and Schneuing, Arne and Segler, Marwin and Correia, Bruno and Roy, Julien and Bengio, Emmanuel and Lio, Pietro",
+    "year": "2025",
+    "venue": "International Conference on Learning Representations",
+    "doi": "",
+    "publication_url": "https://proceedings.iclr.cc/paper_files/paper/2025/hash/7495fa446f10e9edef6e47b2d327596e-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.iclr.cc/paper_files/paper/2025/hash/7495fa446f10e9edef6e47b2d327596e-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "synthemol",
+    "title": "Generative AI for designing and validating easily synthesizable and structurally novel antibiotics",
+    "authors": "Swanson, Kyle and Liu, Gary and Catacutan, Denise B. and Arnold, Autumn and Zou, James and Stokes, Jonathan M.",
+    "year": "2024",
+    "venue": "Nature Machine Intelligence",
+    "doi": "10.1038/s42256-024-00809-7",
+    "publication_url": "https://doi.org/10.1038/s42256-024-00809-7",
+    "metadata_source": "https://doi.org/10.1038/s42256-024-00809-7",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "synthesisdags",
+    "title": "Barking up the right tree: an approach to search over molecule synthesis DAGs",
+    "authors": "Bradshaw, John and Paige, Brooks and Kusner, Matt J. and Segler, Marwin and Hern\\'andez-Lobato, Jos\\'e Miguel",
+    "year": "2020",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2020/hash/4cc05b35c2f937c5bd9e7d41d3686fff-Abstract.html",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2020/hash/4cc05b35c2f937c5bd9e7d41d3686fff-Abstract.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "synthesizable",
+    "title": "A Model to Search for Synthesizable Molecules",
+    "authors": "Bradshaw, John and Paige, Brooks and Kusner, Matt J and Segler, Marwin and Hern\\'{a}ndez-Lobato, Jos\\'{e} Miguel",
+    "year": "2019",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2019/file/46d0671dd4117ea366031f87f3aa0093-Paper.pdf",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2019/hash/46d0671dd4117ea366031f87f3aa0093-Abstract.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "targetdiff",
+    "title": "{D}ecomp{D}iff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design",
+    "authors": "Guan, Jiaqi and Zhou, Xiangxin and Yang, Yuwei and Bao, Yu and Peng, Jian and Ma, Jianzhu and Liu, Qiang and Wang, Liang and Gu, Quanquan",
+    "year": "2023",
+    "venue": "Proceedings of the 40th International Conference on Machine Learning",
+    "doi": "",
+    "publication_url": "https://proceedings.mlr.press/v202/guan23a.html",
+    "metadata_source": "https://proceedings.mlr.press/v202/guan23a.html",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "tb",
+    "title": "Trajectory balance: Improved credit assignment in GFlowNets",
+    "authors": "Whitammer, Esmeralda S. and Jain, Moksh and Bengio, Emmanuel and Sun, Chen and Bengio, Yoshua",
+    "year": "2022",
+    "venue": "Advances in Neural Information Processing Systems",
+    "doi": "10.52202/068431-0431",
+    "publication_url": "https://proceedings.neurips.cc/paper_files/paper/2022/hash/27b51baca8377a0cf109f6ecc15a0f70-Abstract-Conference.html",
+    "metadata_source": "https://proceedings.neurips.cc/paper_files/paper/2022/hash/27b51baca8377a0cf109f6ecc15a0f70-Abstract-Conference.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "tdc",
+    "title": "Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development",
+    "authors": "Huang, Kexin and Fu, Tianfan and Gao, Wenhao and Zhao, Yue and Roohani, Yusuf and Leskovec, Jure and Coley, Connor and Xiao, Cao and Sun, Jimeng and Zitnik, Marinka",
+    "year": "2021",
+    "venue": "NeurIPS Datasets and Benchmarks",
+    "doi": "",
+    "publication_url": "https://datasets-benchmarks-proceedings.neurips.cc/paper_files/paper/2021/hash/4c56ff4ce4aaf9573aa5dff913df997a-Abstract-round1.html",
+    "metadata_source": "https://datasets-benchmarks-proceedings.neurips.cc/paper_files/paper/2021/hash/4c56ff4ce4aaf9573aa5dff913df997a-Abstract-round1.html",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher citation metadata imported. Conference year used for proceedings."
+  },
+  {
+    "key": "tong2024minibatchot",
+    "title": "Improving and generalizing flow-based generative models with minibatch optimal transport",
+    "authors": "Alexander Tong and Kilian Fatras and Nikolay Malkin and Guillaume Huguet and Yanlei Zhang and Jarrid Rector-Brooks and Guy Wolf and Yoshua Bengio",
+    "year": "2024",
+    "venue": "Transactions on Machine Learning Research",
+    "doi": "",
+    "publication_url": "https://openreview.net/forum?id=CD9Snc73AW",
+    "metadata_source": "https://jmlr.org/tmlr/papers/bib/CD9Snc73AW.bib",
+    "verified_date": "2026-09-12",
+    "verification": "Official publisher BibTeX imported."
+  },
+  {
+    "key": "vina",
+    "title": "AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading",
+    "authors": "Trott, Oleg and Olson, Arthur J.",
+    "year": "2010",
+    "venue": "Journal of Computational Chemistry",
+    "doi": "10.1002/jcc.21334",
+    "publication_url": "https://doi.org/10.1002/jcc.21334",
+    "metadata_source": "https://api.crossref.org/works/10.1002/jcc.21334",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher-deposited DOI metadata. Print year used when provided."
+  },
+  {
+    "key": "vinaupdate",
+    "title": "AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings",
+    "authors": "Eberhardt, Jerome and Santos-Martins, Diogo and Tillack, Andreas F. and Forli, Stefano",
+    "year": "2021",
+    "venue": "Journal of Chemical Information and Modeling",
+    "doi": "10.1021/acs.jcim.1c00203",
+    "publication_url": "https://doi.org/10.1021/acs.jcim.1c00203",
+    "metadata_source": "https://api.crossref.org/works/10.1021/acs.jcim.1c00203",
+    "verified_date": "2026-09-12",
+    "verification": "Publisher-deposited DOI metadata. Print year used when provided."
+  }
+]

configs/ablations.yaml

@@ -0,0 +1,8 @@
+kind: multiplicity
+multiplicity: 8
+temperature: 0.7
+steps: 1200
+batch_size: 64
+seeds: [0, 1, 2, 3, 4]
+methods: [dooable, tb_uniform, zero_cost, duplicate_endpoints, unnormalized, tb_exact, exact]
+output: results/ablations

configs/budget_integration.yaml

@@ -0,0 +1,11 @@
+parents: data/examples/parents.csv
+reagents: data/examples/reagents.csv
+reactions: data/examples/reactions.json
+property_models: results/validation/property_models
+budgets: [0, 1]
+max_nodes: 100000
+steps: 400
+samples: 100
+seeds: [0]
+methods: [dooable, exact]
+output: results/budget_integration

configs/chemistry_small.yaml

@@ -0,0 +1,10 @@
+graph: results/validation/chemistry_graph.json
+rewards: results/validation/chemistry_rewards.json
+temperature: 0.7
+steps: 1200
+batch_size: 64
+samples: 1000
+seeds: [0]
+methods: [uniform, reference_tilt, tb_uniform, dooable, exact]
+output: results/chemistry_small
+

configs/enamine_local.yaml

@@ -0,0 +1,15 @@
+# Set these paths to the catalog and chemistry inventory supplied for the study.
+parents: data/private/parents.csv.gz
+reagents: data/private/reagents.csv
+reactions: data/private/reactions.json
+parent_limit: 100
+reagent_limit: null
+budgets: [0, 1, 2]
+max_nodes: 100000
+property_models: results/validation/property_models
+temperature: 0.7
+steps: 2000
+samples: 10000
+seeds: [0, 1, 2, 3, 4]
+methods: [uniform, reference_tilt, tb_uniform, dooable, exact]
+output: results/enamine_local

configs/grid.yaml

@@ -0,0 +1,9 @@
+kind: grid
+width: 5
+budget: 6
+temperature: 0.7
+steps: 2000
+batch_size: 64
+seeds: [0, 1, 2, 3, 4]
+methods: [uniform, reference_tilt, tb_uniform, dooable, exact]
+output: results/grid

configs/molecular_public.yaml

@@ -0,0 +1,12 @@
+parents: data/examples/parents.csv
+reagents: data/examples/reagents.csv
+reactions: data/examples/reactions.json
+property_models: results/validation/property_models
+budgets: [0, 1, 2]
+max_nodes: 100000
+temperature: 0.7
+steps: 1200
+samples: 1000
+seeds: [0]
+methods: [uniform, reference_tilt, tb_uniform, dooable, exact]
+output: results/molecular_public

configs/strings.yaml

@@ -0,0 +1,8 @@
+kind: strings
+length: 4
+budget: 2
+temperature: 0.7
+steps: 1200
+seeds: [0]
+methods: [uniform, reference_tilt, tb_uniform, dooable, exact]
+output: results/strings

configs/toy.yaml

@@ -0,0 +1,9 @@
+kind: multiplicity
+multiplicity: 8
+temperature: 0.7
+steps: 1200
+batch_size: 64
+seeds: [0, 1, 2, 3, 4]
+methods: [uniform, reference_tilt, tb_uniform, dooable, exact]
+output: results/toy
+

data/examples/parents.csv

@@ -0,0 +1,14 @@
+id,smiles
+benzoic_acid,O=C(O)c1ccccc1
+nicotinic_acid,O=C(O)c1cccnc1
+isonicotinic_acid,O=C(O)c1ccncc1
+phenylacetic_acid,O=C(O)Cc1ccccc1
+aniline,Nc1ccccc1
+benzylamine,NCc1ccccc1
+phenethylamine,NCCc1ccccc1
+aminopyridine,Nc1ccccn1
+aminobenzoic_acid,Nc1ccc(C(=O)O)cc1
+hydroxybenzoic_acid,O=C(O)c1ccc(O)cc1
+phenol,Oc1ccccc1
+benzyl_alcohol,OCc1ccccc1
+

data/examples/reactions.json

@@ -0,0 +1,7 @@
+[
+  {"id":"amide_acid_parent","name":"Amide coupling, acid parent","smarts":"[C:1](=[O:2])[O;H1:3].[N;H1,H2;!$(N-[C,S,P]=[O,S,N]):4]>>[C:1](=[O:2])[N:4]","cost":1.0},
+  {"id":"amide_amine_parent","name":"Amide coupling, amine parent","smarts":"[N;H1,H2;!$(N-[C,S,P]=[O,S,N]):4].[C:1](=[O:2])[O;H1:3]>>[C:1](=[O:2])[N:4]","cost":1.0},
+  {"id":"ester_acid_parent","name":"Ester coupling, acid parent","smarts":"[C:1](=[O:2])[O;H1:3].[O;H1;!$([O]-[C,S,P]=[O,S,N]):4]>>[C:1](=[O:2])[O:4]","cost":1.2},
+  {"id":"ester_alcohol_parent","name":"Ester coupling, alcohol parent","smarts":"[O;H1;!$([O]-[C,S,P]=[O,S,N]):4].[C:1](=[O:2])[O;H1:3]>>[C:1](=[O:2])[O:4]","cost":1.2}
+]
+

data/examples/reagents.csv

@@ -0,0 +1,15 @@
+id,smiles
+methylamine,CN
+ethylamine,CCN
+isopropylamine,CC(C)N
+cyclopropylamine,NC1CC1
+morpholine,C1COCCN1
+piperidine,C1CCNCC1
+benzylamine,NCc1ccccc1
+acetic_acid,CC(=O)O
+propionic_acid,CCC(=O)O
+benzoic_acid,O=C(O)c1ccccc1
+nicotinic_acid,O=C(O)c1cccnc1
+methanol,CO
+ethanol,CCO
+

docs/data.md

@@ -0,0 +1,38 @@
+# Inputs and data preparation
+
+## Execution graphs
+
+A graph JSON contains `nodes`, `edges`, `root`, and `metadata`. A node has a unique string `id`, a fixed-width numerical `features` list, optional `metadata`, and an `outcome` for terminal nodes. An edge has a unique `id`, `source`, `target`, finite nonnegative `cost`, and an `action` record. Outcomes are canonical and unique across terminal nodes.
+
+Graph construction checks acyclicity, root reachability, terminal identity, and absence of nonterminal dead ends. Cycles in the underlying execution system are represented by adding a step counter to states. Terminal merging occurs after resource states have been created.
+
+`log_rewards.json` maps every canonical outcome to one finite log weight. Missing or extra outcomes are rejected. Costs and route temperature use the same units. The finite-precision implementation is intended for representable positive probabilities and moderate reward ranges.
+
+## Molecular inventory
+
+Parent and reagent inputs have `id,smiles` columns. Case-insensitive aliases include `Enamine_ID`, `catalog_id`, and `code`. Additional columns are retained as metadata. Gzip and tab-delimited inputs are supported. A row limit applies before canonical deduplication. Supplier IDs with the pattern `m_22_654222_29794186` retain chemistry class, supplier reaction ID, and supplier reagent IDs.
+
+Canonicalization uses RDKit isomeric SMILES and requires one connected molecule. Duplicate parent structures share a graph state, with alternative supplier identifiers retained as aliases. Conflicting structures under one supplier identifier raise an error. Salt stripping and tautomer normalization are user-supplied preprocessing choices.
+
+Reaction JSON is a list of records with unique `id`, two-reactant `smarts`, and finite nonnegative `cost`. The first SMARTS reactant is the current molecule. The second is an available reagent. Each successful application consumes one additional reaction. Products are sanitized, canonicalized, deduplicated, and restricted to molecular weight at most 750 Da. The cap is recorded in graph metadata. The purchased parent's own supplier route is recorded separately from the additional-reaction budget.
+
+The shipped templates describe amide and ester graph transformations. Their experimental scope, coupling reagents, solvents, protection requirements, and yields require a chemistry-specific protocol. Replace these examples with the reaction rules and stock restrictions selected for the intended synthesis campaign.
+
+Generation writes JSONL records with `outcome`, `edge_ids`, `edge_indices`, `cost`, `log_probability`, and `actions`. Actions begin with a parent selection, contain zero or more reaction records, and end with stop. Each reaction record contains template ID, SMARTS, reagent ID, reagent SMILES, input, and product.
+
+## Public property data
+
+| Dataset | Released source | Columns | Units |
+|---|---|---|---|
+| Caco-2 Wang | [TDC release on Harvard Dataverse](https://dataverse.harvard.edu/api/access/datafile/4259569) | `Drug`, `Y` | log10 permeability in cm/s |
+| BACE | [MoleculeNet processed release](https://deepchemdata.s3-us-west-1.amazonaws.com/datasets/bace.csv) | `mol`, `pIC50` | pIC50 |
+
+The original Caco-2 study is [Wang et al., JCIM 2016](https://doi.org/10.1021/acs.jcim.5b00642). MoleculeNet is described by [Wu et al., Chemical Science 2018](https://doi.org/10.1039/C7SC02664A). The TDC dataset collection is described in the NeurIPS Datasets and Benchmarks paper cited in `paper/references.bib`.
+
+Downloads are cached locally with SHA-256 checksums and source metadata. Unparseable, disconnected, and nonfinite-label rows are excluded. Canonical duplicates are averaged. Entire Bemis-Murcko scaffold groups are assigned to the 80/20 training/test split. All acyclic molecules share one scaffold group. Split seeds change tie ordering among groups of equal size.
+
+Each predictor uses 1,024-bit radius-two Morgan fingerprints and 256 extra trees, minimum leaf size 2, and feature fraction 0.5. Test labels are used for reported MAE and R². The molecular state encoder uses 128 Morgan bits plus consumed budget, terminal, and root indicators. These two feature widths serve different computations.
+
+Public generation utilities are `clip((predicted_BACE_pIC50 - 4)/5, 0, 1)` and `clip((predicted_Caco2 + 7)/3, 0, 1)`. The default log reward is five times their equally weighted mean. QED, logP, and size rewards are available when `dooable score` is called without property models.
+
+Raw download archives are omitted from this repository. Split membership, held-out predictions, source records, and fitted weights accompany the executed runs. Upstream dataset and publication terms apply to those sources. The small named-compound fixtures and generated route records were created for this implementation. No licensed Enamine catalog or credentials are included.

docs/environment.json

@@ -0,0 +1,17 @@
+{
+  "python": "3.12.14 (main, Aug 25 2026, 14:00:49) [Clang 22.1.3 ]",
+  "versions": {
+    "torch": "2.14.0+cpu",
+    "rdkit": "2026.03.6",
+    "sklearn": "1.8.0",
+    "numpy": "2.3.5",
+    "scipy": "1.18.1",
+    "pandas": "3.0.5",
+    "matplotlib": "3.10.8",
+    "requests": "2.34.2",
+    "yaml": "6.0.3",
+    "joblib": "1.5.3",
+    "pytest": "9.1.1"
+  },
+  "device": "CPU"
+}

docs/experiments.md

@@ -0,0 +1,54 @@
+# Manuscript experiments and commands
+
+The manuscript contains unfilled scientific-result tables and empirical plot layouts. Executed reference runs are stored separately under `results/`. Their graph sizes and metrics are listed in `validation.md`.
+
+| Manuscript item | Workflow | Remaining experiment |
+|---|---|---|
+| Figure 1 | Editable TikZ and molecule-rendering source in `assets/figure1_source/` | Final formulation diagram included |
+| Table 1, discrete generation | `run_benchmarks.py` with `toy.yaml`, `grid.yaml`, `strings.yaml` | Larger held-out graph-instance study, SubTB, and learned-backward TLM comparator |
+| Figure 2, distribution diagnostics | `sweep_exact.py`, saved `training.json`, `plot_results.py` | Full five-seed sweep over all specified graph families |
+| Table 2, molecular construction | `run_molecular.py` with `molecular_public.yaml` or `enamine_local.yaml`; `evaluate_candidates.py` | Licensed inventory and matched third-party generators |
+| Table 3, molecular properties | `fit-properties`, `score`, generation, candidate evaluation | LIT-PCBA docking, full target panel, and external baselines |
+| Figure 3, preferences and scaling | `sweep_preferences.py`; repeated local-inventory configurations | Full target-specific preference grid and measured catalog scaling |
+| Table 4, ablations | `run_benchmarks.py --config configs/ablations.yaml` | Matched molecular ablations and larger graph instances |
+| Table 5, scaling | `run_molecular.py` with parent limits 100, 1000, 10000 | Licensed catalog expansion, peak-memory measurements, full timing sweep |
+| Supplement, reaction budgets | `molecular_public.yaml` runs B = 0, 1, 2 | Full target inventory and matched external methods |
+| Supplement, target-specific docking | Common candidate records and receptor/grid protocol | Fifteen prepared target pockets and external generator integrations |
+| Supplement, property prediction | `dooable fit-properties` | Five split seeds and selected released molecular encoder |
+
+## Implemented comparisons
+
+`uniform` assigns equal mass to outgoing actions. `reference_tilt` reweights that path process by terminal reward through a backward value recursion. `tb_uniform` learns a forward trajectory-balance sampler against locally uniform backward probabilities. `dooable` fits the cost-dependent backward prefix values and forward trajectory balance. `exact` uses both dynamic programs.
+
+`zero_cost` sets every edge cost to zero for the conditional route law. `duplicate_endpoints` assigns a separate terminal reward to each incoming stop edge and evaluates the resulting policy after canonical merging. `unnormalized` uses learned prefix differences directly in the backward path weights during trajectory-balance training. `tb_exact` uses the exact cost-dependent backward policy during forward learning.
+
+The cost-free and duplicated-endpoint comparisons use exact forward construction to isolate the corresponding distributional change. Their runtimes therefore describe the exact ablation, while learned-policy runtimes include training. Comparisons of optimization speed should group methods by solver mode.
+
+## External comparisons
+
+The following original implementations require integration with the selected inventory and scoring protocol. They have not been run in this package.
+
+| Method | Verified primary publication | Required integration |
+|---|---|---|
+| SynFlowNet | ICLR 2025, `synflownet` citation | Parent selection, matched reaction/reagent inventory, candidate and route export |
+| RxnFlow | ICLR 2025, `rxnflow` citation | Inventory conversion, reward callback, route export |
+| CGFlow | ICML 2025, `cgflow` citation | Prepared target pockets, pose handling, matched synthesis actions |
+| SyntheMol | Nature Machine Intelligence 2024, `synthemol` citation | Matched construction inventory, score callback, search-call accounting |
+| SubTB | ICML 2023, `subtb` citation | Identical graph and reward, original subtrajectory objective |
+| TB with learned backward TLM | ICLR 2025, `backward` citation | Original backward-policy training objective |
+
+These method names refer to their original published implementations. External outputs should provide one canonical structure and its full construction record per candidate, with method, seed, target, budget, requested count, and oracle-call accounting. Adapt native route records to the `actions` schema in `data.md` before replay.
+
+## Scoring and split protocol
+
+The public example uses measured BACE inhibition and Caco-2 transport to fit separate property predictors. Full target-pocket experiments require target-specific docking. Fix receptor preparation, protonation, ligand preparation, docking grids, Vina version, exhaustiveness, and random seeds before comparing methods. Docking energies use kcal/mol. Record raw energies separately from normalized reward utilities.
+
+Select clipping bounds and hyperparameters on the validation partition. Group parents by Bemis-Murcko scaffold before generating descendants. Resolve products shared across parent partitions into one partition before held-out evaluation. The included small graph experiments optimize one supplied graph per run. Generalization across disjoint graph instances is a separate experiment.
+
+Count every unique oracle evaluation, including scores used during support construction or preprocessing. Store cached scores and reuse them within a declared experiment. For the 168-outcome public graph, the scoring step evaluates all 168 outcomes before training. Sampling counts are recorded separately.
+
+The current public evaluator reports two-dimensional hypervolume over predicted BACE and Caco-2 utilities. The full docking study uses affinity and permeability utilities on the same normalized axes. QED and internal diversity are additional readouts. Report undefined summaries as missing when fewer than the required candidates are available.
+
+## Citation verification
+
+`bibliography/verified_references.csv` and `.json` contain 72 references, each with authors, publication year, venue, primary publication URL, metadata source, and verification date. Publisher BibTeX, official conference records, journal citation metadata, and publisher-deposited Crossref records were used. Conference versions replace corresponding preprints. Strong Stochastic Flow Maps is identified as an ICML workshop contribution.

docs/formulation.md

@@ -0,0 +1,31 @@
+# Formulation and implementation
+
+Let a finite rooted DAG encode executable paths within a resource budget. Each canonical outcome has one terminal node. The prescribed endpoint law is `pi(y) = r(y) / sum(r)`. Among path distributions with that endpoint law, minimize expected execution cost minus route temperature times conditional path entropy.
+
+The optimal conditional route probability is proportional to `exp(-C(path)/tau)` among paths to the same outcome. Its normalization is a prefix partition evaluated at the terminal node. The exact prefix recursion is
+
+$$v(s_0)=0,\qquad v(s)=\log\sum_{e:u\to s}\exp\{v(u)-c(e)/\tau\}.$$
+
+The backward edge law is the softmax of predecessor values minus edge costs divided by temperature. Products of these probabilities telescope to the conditional route law. Terminal demand starts at `pi`, propagates backward through this law, and is reversed to obtain an exact forward policy.
+
+The neural implementation uses separate two-layer SiLU networks for prefix values and forward edge logits. Prefix fitting uses detached log-sum-exp targets over every incoming edge. The root value is fixed to zero. Forward training minimizes squared trajectory-balance residuals with the backward probabilities detached. A mixture of current and uniform policies collects paths. Every training run uses a fixed graph, reward vector, and temperature.
+
+The normalizer is initialized to the log of the outcome count plus the mean log reward and remains trainable. This initialization improves the scalar warmup on the small reaction graph. The implementation records the resulting training history. `--initialize` reuses network parameters for another reward vector on the same graph. `--resume` restores network and optimizer state for the same run.
+
+## Error statements
+
+The manuscript proves the unique conditional optimum and a decomposition of endpoint and route error. If the absolute trajectory residual is at most eta over every feasible path, the endpoint TV is at most `tanh(eta)`. If every prefix-recursion residual is also at most epsilon and path length is at most H edges, joint KL is at most `2 eta + 2 H epsilon`. At exact trajectory balance, the conditional objective excess is at most `2 tau H epsilon`.
+
+These are full-support deterministic statements. Minibatch loss measurements are recorded training diagnostics. The code tests the identities on exactly enumerable graphs and compares dynamic programming against explicit path sums.
+
+For a learned sampler whose endpoint law differs from pi, the reported conditional gap is
+
+$$\tau\sum_y P_Y(y)\,\mathrm{KL}\bigl(P(\cdot\mid y)\Vert Q^*(\cdot\mid y)\bigr).$$
+
+It equals temperature times joint KL minus endpoint KL. This metric separates route quality from endpoint distribution error. At exact endpoint alignment, it equals the difference in the constrained objective.
+
+## Computational scope
+
+The algorithms use complete incoming and outgoing edge sets on the stored graph. Graph materialization and oracle scoring precede learning in the reference workflow. Dynamic-programming passes are linear in stored nodes and edges. Molecular expansion can grow rapidly with the parent inventory, reagent count, and reaction budget.
+
+The executable graph is the declared support of a run. Full-catalog coverage requires a complete expansion or another complete predecessor construction. The current repository implements materialized graphs and records the selected inventory. Distributed catalog expansion, sampled predecessor estimation, and a single model jointly conditioned on multiple graph budgets remain extensions.

docs/package_verification.json

@@ -0,0 +1,15 @@
+{
+  "main_pages": 8,
+  "total_pages": 20,
+  "references": 72,
+  "overfull_boxes": 0,
+  "unresolved_citations": 0,
+  "figure_copies_identical": true,
+  "figure_sha256": "198a5a6880f73f348b59847dd75f41c025a4ec9196b588b7da3bb397aeeefa4a",
+  "verification_date": "2026-09-12",
+  "repository_installation": "Fresh virtual environment from extracted ZIP, reusing installed dependencies",
+  "tests_passed": 24,
+  "workflow_commands_passed": 12,
+  "sampled_chemical_routes_replayed": 50,
+  "sampled_chemical_routes_total": 50
+}

docs/validation.md

@@ -0,0 +1,37 @@
+# Completed validation
+
+Validation used CPU execution with the versions in `environment.json`. Numerical results below are measured outputs from the included runs. The manuscript retains placeholders for its main scientific comparisons.
+
+## End-to-end data checks
+
+| Dataset | Clean molecules | Train | Test | MAE | R² |
+|---|---:|---:|---:|---:|---:|
+| CACO2 | 897 | 717 | 180 | 0.4454 | 0.4707 |
+| BACE | 1513 | 1210 | 303 | 0.6474 | 0.5823 |
+
+Caco-2 MAE uses log10(cm/s). BACE MAE uses pIC50. Both fits use scaffold groups, split seed 0, and 256 extra trees. Downloaded data were parsed and canonicalized before splitting. Source checksums, split assignments, test predictions, and fitted weights are included.
+
+## Generative reference runs
+
+| System | Nodes | Edges | Outcomes | Seeds | Updates | DooABLe endpoint TV | Conditional gap |
+|---|---:|---:|---:|---:|---:|---:|---:|
+| Multiplicity | 12 | 18 | 2 | 5 | 1200 | 5.6311e-05 | 1.6247e-07 |
+| Lattice | 67 | 147 | 22 | 5 | 2000 | 0.0519513 | 0.148841 |
+| String edits | 35 | 60 | 16 | 1 | 1200 | 0.00411287 | 0.00049674 |
+| Reaction graph | 337 | 410 | 168 | 1 | 1200 | 0.000863913 | 1.01626e-05 |
+
+Conditional gaps use route-cost units and temperature 0.7. Per-seed values, standard errors, and comparator measurements are stored with each run. The lattice and string runs have lower endpoint TV under uniform-backward trajectory balance at the recorded training budgets. DooABLe has lower conditional route divergence on those runs. These mixed outcomes are retained in the supplied CSV files.
+
+The reaction graph contains 12 parents, 13 reagents, four directional templates, and a budget of two additional reactions. All 1,000 DooABLe samples replayed successfully, with 166 unique outcomes. Scoring evaluated all 168 canonical outcomes before learning. Mean reaction count among the sampled routes was 1.395. Property summaries in `results/chemistry_small/candidates.json` are model predictions.
+
+The ablation run uses five seeds and tests uniform backward probabilities, zero execution cost, duplicated terminal outcomes, unnormalized backward weights, and exact prefix values. The exact sweep includes 50 multiplicity/temperature comparisons. The public preference sweep includes 15 exact reward settings. Budget-integration runs exercise the complete molecular runner at B = 0 and B = 1 with 400 updates and 100 samples.
+
+## Software checks
+
+The 24 tests cover exact path sums, endpoint normalization, cost/temperature behavior, deterministic error bounds, cycles, budgeted expansion, chemical replay, duplicate identifiers, scaffold isolation, serialization, checkpoint reload, and resumed-training equivalence.
+
+The documented public workflow was executed from data download through property fitting, graph construction, neural training, sampling, replay, candidate evaluation, and plot export. Existing weights support immediate inference. New training checkpoints contain optimizer state for resumption.
+
+Full licensed-catalog generation, held-out graph-instance generalization, LIT-PCBA docking, learned molecular encoders, and the original third-party baselines remain unexecuted. Their concrete dependencies are listed in `experiments.md`.
+
+The final ZIP files were extracted into clean directories. The manuscript compiled to eight main pages and 20 total pages, with 72 references, zero unresolved citations, and zero overfull boxes. The repository was installed into a fresh virtual environment using the recorded installed dependencies. All 24 tests passed. CLI checks covered toy training, checkpoint resumption, sampling, chemistry graph construction, property scoring with the included weights, exact sampling, and replay of 50 chemical routes. Figure 1 is identical in the manuscript and repository.

paper/DooABLe_ICML.pdf

@@ -0,0 +1,3 @@
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+oid sha256:6a8fdb5cab42069033a7fa8ab8882ee870e8026dc0c390fb810b8e70ac330490
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paper/algorithm.sty

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+% ALGORITHM STYLE -- Released 8 April 1996
+%    for LaTeX-2e
+% Copyright -- 1994 Peter Williams
+% E-mail Peter.Williams@dsto.defence.gov.au
+\NeedsTeXFormat{LaTeX2e}
+\ProvidesPackage{algorithm}
+\typeout{Document Style `algorithm' - floating environment}
+
+\RequirePackage{float}
+\RequirePackage{ifthen}
+\newcommand{\ALG@within}{nothing}
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+\newcommand{\listalgorithmname}{List of \ALG@name s}
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+% Declare Options
+% first appearance
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+}
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+}
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+}
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+  \renewcommand{\ALG@within}{part}
+  \setboolean{ALG@within}{true}
+}
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+}
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+}
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+}
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+  \ifthenelse{\equal{\ALG@within}{section}}
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+  \ifthenelse{\equal{\ALG@within}{subsection}}
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+  \ifthenelse{\equal{\ALG@within}{subsubsection}}
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+  \ifthenelse{\equal{\ALG@within}{nothing}}
+     {\newfloat{algorithm}{htbp}{loa}}{}
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+\floatname{algorithm}{\ALG@name}
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+\newcommand{\listofalgorithms}{\listof{algorithm}{\listalgorithmname}}
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paper/algorithmic.sty

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+% ALGORITHMIC STYLE -- Released 8 APRIL 1996
+%    for LaTeX version 2e
+% Copyright -- 1994 Peter Williams
+% E-mail PeterWilliams@dsto.defence.gov.au
+%
+% Modified by Alex Smola (08/2000)
+% E-mail Alex.Smola@anu.edu.au
+%
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+\newcommand{\algorithmicrepeat}{\textbf{repeat}}
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+
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+{}{\ \algorithmiccomment{##1}}}
+  \newcommand{\REQUIRE}{\item[\algorithmicrequire]}
+  \newcommand{\ENSURE}{\item[\algorithmicensure]}
+  \newcommand{\STATE}{\ALC@it}
+  \newcommand{\COMMENT}[1]{\algorithmiccomment{##1}}
+%changes by alex smola
+  \newcommand{\INPUT}{\item[\algorithmicinput]}
+  \newcommand{\OUTPUT}{\item[\algorithmicoutput]}
+  \newcommand{\SET}{\item[\algorithmicset]}
+%  \newcommand{\TRUE}{\algorithmictrue}
+%  \newcommand{\FALSE}{\algorithmicfalse}
+  \newcommand{\AND}{\algorithmicand}
+  \newcommand{\OR}{\algorithmicor}
+  \newenvironment{ALC@func}{\begin{ALC@g}}{\end{ALC@g}}
+  \newenvironment{ALC@main}{\begin{ALC@g}}{\end{ALC@g}}
+%end changes by alex smola
+  \newenvironment{ALC@if}{\begin{ALC@g}}{\end{ALC@g}}
+  \newenvironment{ALC@for}{\begin{ALC@g}}{\end{ALC@g}}
+  \newenvironment{ALC@whl}{\begin{ALC@g}}{\end{ALC@g}}
+  \newenvironment{ALC@loop}{\begin{ALC@g}}{\end{ALC@g}}
+  \newenvironment{ALC@rpt}{\begin{ALC@g}}{\end{ALC@g}}
+  \renewcommand{\\}{\@centercr}
+  \newcommand{\IF}[2][default]{\ALC@it\algorithmicif\ ##2\ \algorithmicthen%
+\ALC@com{##1}\begin{ALC@if}}
+  \newcommand{\SHORTIF}[2]{\ALC@it\algorithmicif\ ##1\
+    \algorithmicthen\ {##2}}
+  \newcommand{\ELSE}[1][default]{\end{ALC@if}\ALC@it\algorithmicelse%
+\ALC@com{##1}\begin{ALC@if}}
+  \newcommand{\ELSIF}[2][default]%
+{\end{ALC@if}\ALC@it\algorithmicelsif\ ##2\ \algorithmicthen%
+\ALC@com{##1}\begin{ALC@if}}
+  \newcommand{\FOR}[2][default]{\ALC@it\algorithmicfor\ ##2\ \algorithmicdo%
+\ALC@com{##1}\begin{ALC@for}}
+  \newcommand{\FORALL}[2][default]{\ALC@it\algorithmicforall\ ##2\ %
+\algorithmicdo%
+\ALC@com{##1}\begin{ALC@for}}
+  \newcommand{\SHORTFORALL}[2]{\ALC@it\algorithmicforall\ ##1\ %
+    \algorithmicdo\ {##2}}
+  \newcommand{\WHILE}[2][default]{\ALC@it\algorithmicwhile\ ##2\ %
+\algorithmicdo%
+\ALC@com{##1}\begin{ALC@whl}}
+  \newcommand{\LOOP}[1][default]{\ALC@it\algorithmicloop%
+\ALC@com{##1}\begin{ALC@loop}}
+%changed by alex smola
+  \newcommand{\FUNCTION}[2][default]{\ALC@it\algorithmicfunction\ ##2\ %
+    \ALC@com{##1}\begin{ALC@func}}
+  \newcommand{\MAIN}[2][default]{\ALC@it\algorithmicmain\ ##2\ %
+    \ALC@com{##1}\begin{ALC@main}}
+%end changed by alex smola
+  \newcommand{\REPEAT}[1][default]{\ALC@it\algorithmicrepeat%
+    \ALC@com{##1}\begin{ALC@rpt}}
+    \newcommand{\UNTIL}[1]{\end{ALC@rpt}\ALC@it\algorithmicuntil\ ##1}
+  \ifthenelse{\boolean{ALC@noend}}{
+    \newcommand{\ENDIF}{\end{ALC@if}}
+    \newcommand{\ENDFOR}{\end{ALC@for}}
+    \newcommand{\ENDWHILE}{\end{ALC@whl}}
+    \newcommand{\ENDLOOP}{\end{ALC@loop}}
+    \newcommand{\ENDFUNCTION}{\end{ALC@func}}
+    \newcommand{\ENDMAIN}{\end{ALC@main}}
+  }{
+    \newcommand{\ENDIF}{\end{ALC@if}\ALC@it\algorithmicendif}
+    \newcommand{\ENDFOR}{\end{ALC@for}\ALC@it\algorithmicendfor}
+    \newcommand{\ENDWHILE}{\end{ALC@whl}\ALC@it\algorithmicendwhile}
+    \newcommand{\ENDLOOP}{\end{ALC@loop}\ALC@it\algorithmicendloop}
+    \newcommand{\ENDFUNCTION}{\end{ALC@func}\ALC@it\algorithmicendfunction}
+    \newcommand{\ENDMAIN}{\end{ALC@main}\ALC@it\algorithmicendmain}
+  } 
+  \renewcommand{\@toodeep}{}
+  \begin{list}{\ALC@lno}{\setcounter{ALC@line}{0}\setcounter{ALC@rem}{0}%
+      \itemsep\z@ \itemindent\z@ \listparindent\z@%
+      \partopsep\z@ \parskip\z@ \parsep\z@%
+      \labelsep 0.5em \topsep 0.2em%
+      \ifthenelse{\equal{#1}{0}}
+      {\labelwidth 0.5em }
+      {\labelwidth  1.2em }
+      \leftmargin\labelwidth \addtolength{\leftmargin}{\labelsep}
+      \ALC@tlm\labelsep
+      }
+    }
+  {\end{list}}
+
+
+
+
+
+
+
+
+
+
+
+
+
+

paper/fancyhdr.sty

@@ -0,0 +1,864 @@
+%%
+%% This is file `fancyhdr.sty',
+%% generated with the docstrip utility.
+%%
+%% The original source files were:
+%%
+%% fancyhdr.dtx  (with options: `fancyhdr')
+%% 
+%% This is a generated file.
+%% 
+%% This file may be distributed and/or modified under the conditions of
+%% the LaTeX Project Public License, either version 1.3 of this license
+%% or (at your option) any later version.  The latest version of this
+%% license is in:
+%% 
+%%    http://www.latex-project.org/lppl.txt
+%% 
+%% and version 1.3 or later is part of all distributions of LaTeX version
+%% 2005/12/01 or later.
+%% 
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\NeedsTeXFormat{LaTeX2e}[2018-04-01]
+\ProvidesPackage{fancyhdr}%
+           [2025/02/07 v5.2
+                  Extensive control of page headers and footers]%
+% Copyright (C) 1994-2025 by Pieter van Oostrum <pieter@vanoostrum.org>
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+\ifdefined\NewDocumentCommand\else\RequirePackage{xparse}\fi
+\newif\iff@nch@check
+\f@nch@checktrue
+\DeclareOption{nocheck}{%
+  \f@nch@checkfalse
+}
+\let\f@nch@gbl\relax
+\newif\iff@nch@compatViii
+\DeclareOption{compatV3}{%
+  \PackageWarningNoLine{fancyhdr}{The `compatV3' option is deprecated.\MessageBreak
+    It will disappear in one of the following releases.\MessageBreak
+    Please change your document to work\MessageBreak
+    without this option}
+  \let\f@nch@gbl\global
+  \f@nch@compatViiitrue
+}
+\newif\iff@nch@twoside
+\f@nch@twosidefalse
+\DeclareOption{twoside}{%
+  \if@twoside\else\f@nch@twosidetrue\fi
+}
+\newcommand\f@nch@def[2]{%
+  \def\temp@a{#2}\ifx\temp@a\@empty\f@nch@gbl\def#1{}%
+                 \else\f@nch@gbl\def#1{#2\strut}\fi}
+\DeclareOption{myheadings}{%
+  \@ifundefined{chapter}{%
+    \def\ps@myheadings{\ps@f@nch@fancyproto \let\@mkboth\@gobbletwo
+      \fancyhf{}
+      \fancyhead[LE,RO]{\thepage}%
+      \fancyhead[RE]{\slshape\leftmark}%
+      \fancyhead[LO]{\slshape\rightmark}%
+      \let\sectionmark\@gobble
+      \let\subsectionmark\@gobble
+    }%
+  }%
+  {\def\ps@myheadings{\ps@f@nch@fancyproto \let\@mkboth\@gobbletwo
+      \fancyhf{}
+      \fancyhead[LE,RO]{\thepage}%
+      \fancyhead[RE]{\slshape\leftmark}%
+      \fancyhead[LO]{\slshape\rightmark}%
+      \let\chaptermark\@gobble
+      \let\sectionmark\@gobble
+    }%
+  }%
+}
+\DeclareOption{headings}{%
+  \@ifundefined{chapter}{%
+    \if@twoside
+      \def\ps@headings{\ps@f@nch@fancyproto \def\@mkboth{\protect\markboth}
+        \fancyhf{}
+        \fancyhead[LE,RO]{\thepage}%
+        \fancyhead[RE]{\slshape\leftmark}%
+        \fancyhead[LO]{\slshape\rightmark}%
+        \def\sectionmark##1{%
+          \markboth{\MakeUppercase{%
+            \ifnum \c@secnumdepth >\z@ \thesection\quad \fi##1}}{}}%
+        \def\subsectionmark##1{%
+          \markright{%
+            \ifnum \c@secnumdepth >\@ne \thesubsection\quad \fi##1}}%
+      }%
+    \else
+      \def\ps@headings{\ps@f@nch@fancyproto \def\@mkboth{\protect\markboth}
+        \fancyhf{}
+        \fancyhead[LE,RO]{\thepage}%
+        \fancyhead[RE]{\slshape\leftmark}%
+        \fancyhead[LO]{\slshape\rightmark}%
+        \def\sectionmark##1{%
+          \markright {\MakeUppercase{%
+            \ifnum \c@secnumdepth >\z@ \thesection\quad \fi##1}}}%
+        \let\subsectionmark\@gobble % Not needed but inserted for safety
+      }%
+    \fi
+  }{\if@twoside
+      \def\ps@headings{\ps@f@nch@fancyproto \def\@mkboth{\protect\markboth}
+        \fancyhf{}
+        \fancyhead[LE,RO]{\thepage}%
+        \fancyhead[RE]{\slshape\leftmark}%
+        \fancyhead[LO]{\slshape\rightmark}%
+        \def\chaptermark##1{%
+          \markboth{\MakeUppercase{%
+            \ifnum \c@secnumdepth >\m@ne \if@mainmatter
+              \@chapapp\ \thechapter. \ \fi\fi##1}}{}}%
+        \def\sectionmark##1{%
+          \markright {\MakeUppercase{%
+            \ifnum \c@secnumdepth >\z@ \thesection. \ \fi##1}}}%
+      }%
+    \else
+      \def\ps@headings{\ps@f@nch@fancyproto \def\@mkboth{\protect\markboth}
+        \fancyhf{}
+        \fancyhead[LE,RO]{\thepage}%
+        \fancyhead[RE]{\slshape\leftmark}%
+        \fancyhead[LO]{\slshape\rightmark}%
+        \def\chaptermark##1{%
+          \markright{\MakeUppercase{%
+            \ifnum \c@secnumdepth >\m@ne \if@mainmatter
+              \@chapapp\ \thechapter. \ \fi\fi##1}}}%
+        \let\sectionmark\@gobble % Not needed but inserted for safety
+      }%
+    \fi
+  }%
+}
+\ProcessOptions*
+\newcommand{\f@nch@forc}[3]{\expandafter\f@nchf@rc\expandafter#1\expandafter{#2}{#3}}
+\newcommand{\f@nchf@rc}[3]{\def\temp@ty{#2}\ifx\@empty\temp@ty\else
+                                    \f@nch@rc#1#2\f@nch@rc{#3}\fi}
+\long\def\f@nch@rc#1#2#3\f@nch@rc#4{\def#1{#2}#4\f@nchf@rc#1{#3}{#4}}
+\newcommand{\f@nch@for}[3]{\edef\@fortmp{#2}%
+  \expandafter\@forloop#2,\@nil,\@nil\@@#1{#3}}
+\newcommand\f@nch@default[3]{%
+  \edef\temp@a{\lowercase{\edef\noexpand\temp@a{#3}}}\temp@a \def#1{}%
+  \f@nch@forc\tmpf@ra{#2}%
+  {\expandafter\f@nch@ifin\tmpf@ra\temp@a{\edef#1{#1\tmpf@ra}}{}}%
+  \ifx\@empty#1\def#1{#2}\fi}
+\newcommand{\f@nch@ifin}[4]{%
+  \edef\temp@a{#2}\def\temp@b##1#1##2\temp@b{\def\temp@b{##1}}%
+  \expandafter\temp@b#2#1\temp@b\ifx\temp@a\temp@b #4\else #3\fi}
+\newcommand{\fancyhead}[2][]{\f@nch@fancyhf\fancyhead h[#1]{#2}}%
+\newcommand{\fancyfoot}[2][]{\f@nch@fancyhf\fancyfoot f[#1]{#2}}%
+\newcommand{\fancyhf}[2][]{\f@nch@fancyhf\fancyhf {}[#1]{#2}}%
+\newcommand{\fancyheadoffset}[2][]{\f@nch@fancyhfoffs\fancyheadoffset h[#1]{#2}}%
+\newcommand{\fancyfootoffset}[2][]{\f@nch@fancyhfoffs\fancyfootoffset f[#1]{#2}}%
+\newcommand{\fancyhfoffset}[2][]{\f@nch@fancyhfoffs\fancyhfoffset {}[#1]{#2}}%
+\def\f@nch@fancyhf@Echeck#1{%
+  \if@twoside\else
+    \iff@nch@twoside\else
+      \if\f@nch@@eo e%
+        \PackageWarning{fancyhdr} {\string#1's `E' option without twoside option is useless.\MessageBreak
+          Please consider using the `twoside' option}%
+  \fi\fi\fi
+}
+\long\def\f@nch@fancyhf#1#2[#3]#4{%
+  \def\temp@c{}%
+  \f@nch@forc\tmpf@ra{#3}%
+  {\expandafter\f@nch@ifin\tmpf@ra{eolcrhf,EOLCRHF}%
+    {}{\edef\temp@c{\temp@c\tmpf@ra}}}%
+  \ifx\@empty\temp@c\else \PackageError{fancyhdr}{Illegal char `\temp@c' in
+    \string#1 argument: [#3]}{}%
+  \fi \f@nch@for\temp@c{#3}%
+  {\f@nch@default\f@nch@@eo{eo}\temp@c
+    \f@nch@fancyhf@Echeck{#1}%
+    \f@nch@default\f@nch@@lcr{lcr}\temp@c
+    \f@nch@default\f@nch@@hf{hf}{#2\temp@c}%
+    \f@nch@forc\f@nch@eo\f@nch@@eo
+        {\f@nch@forc\f@nch@lcr\f@nch@@lcr
+          {\f@nch@forc\f@nch@hf\f@nch@@hf
+            {\expandafter\f@nch@def\csname
+              f@nch@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname {#4}}}}}}
+\def\f@nch@fancyhfoffs#1#2[#3]#4{%
+  \def\temp@c{}%
+  \f@nch@forc\tmpf@ra{#3}%
+  {\expandafter\f@nch@ifin\tmpf@ra{eolrhf,EOLRHF}%
+    {}{\edef\temp@c{\temp@c\tmpf@ra}}}%
+  \ifx\@empty\temp@c\else \PackageError{fancyhdr}{Illegal char `\temp@c' in
+    \string#1 argument: [#3]}{}%
+  \fi \f@nch@for\temp@c{#3}%
+  {\f@nch@default\f@nch@@eo{eo}\temp@c
+    \f@nch@fancyhf@Echeck{#1}%
+    \f@nch@default\f@nch@@lcr{lr}\temp@c
+    \f@nch@default\f@nch@@hf{hf}{#2\temp@c}%
+    \f@nch@forc\f@nch@eo\f@nch@@eo
+        {\f@nch@forc\f@nch@lcr\f@nch@@lcr
+          {\f@nch@forc\f@nch@hf\f@nch@@hf
+            {\expandafter\setlength\csname
+              f@nch@offset@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname {#4}}}}}%
+  \f@nch@setoffs}
+\NewDocumentCommand {\fancyheadwidth}{ s O{} O{} m }
+                      {\f@nch@fancyhfwidth{#1}\fancyheadwidth h[#2][#3]{#4}}%
+\NewDocumentCommand {\fancyfootwidth}{ s O{} O{} m }
+                      {\f@nch@fancyhfwidth{#1}\fancyfootwidth f[#2][#3]{#4}}%
+\NewDocumentCommand {\fancyhfwidth}  { s O{} O{} m }
+                      {\f@nch@fancyhfwidth{#1}\fancyhfwidth  {}[#2][#3]{#4}}%
+\def\f@nch@fancyhfwidth#1#2#3[#4][#5]#6{%
+  \setlength\@tempdima{#6}%
+  \def\temp@c{}%
+  \f@nch@forc\tmpf@ra{#4}%
+  {\expandafter\f@nch@ifin\tmpf@ra{eolcrhf,EOLCRHF}%
+    {}{\edef\temp@c{\temp@c\tmpf@ra}}}%
+  \ifx\@empty\temp@c\else \PackageError{fancyhdr}{Illegal char `\temp@c' in
+    \string#2 argument: [#4]}{}%
+  \fi
+  \f@nch@for\temp@c{#4}%
+  {\f@nch@default\f@nch@@eo{eo}\temp@c
+    \f@nch@fancyhf@Echeck{#2}%
+    \f@nch@default\f@nch@@lcr{lcr}\temp@c
+    \f@nch@default\f@nch@@hf{hf}{#3\temp@c}%
+    \f@nch@forc\f@nch@eo\f@nch@@eo
+        {\f@nch@forc\f@nch@lcr\f@nch@@lcr
+          {\f@nch@forc\f@nch@hf\f@nch@@hf
+            {%
+              \IfBooleanTF{#1}{%
+                \expandafter\edef\csname
+                  f@nch@width@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname{\the\@tempdima}%
+              }%
+              {%
+                \expandafter\def\csname
+                  f@nch@width@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname{#6}%
+              }%
+              \csname f@nchdrwdt@align@v@\f@nch@hf\endcsname
+              \edef\f@nch@align@@h{\f@nch@lcr}%
+              \def\temp@a{#5}%
+              \ifx\temp@a\@empty \else \f@nchdrwdt@align#5\@nil{#2}\fi
+              \expandafter\edef\csname
+                f@nch@align@\f@nch@eo\f@nch@lcr\f@nch@hf\endcsname
+                   {\f@nch@align@@v\f@nch@align@@h}}}}}}
+\def\f@nch@width@elh{\headwidth}
+\def\f@nch@width@ech{\headwidth}
+\def\f@nch@width@erh{\headwidth}
+\def\f@nch@width@olh{\headwidth}
+\def\f@nch@width@och{\headwidth}
+\def\f@nch@width@orh{\headwidth}
+\def\f@nch@width@elf{\headwidth}
+\def\f@nch@width@ecf{\headwidth}
+\def\f@nch@width@erf{\headwidth}
+\def\f@nch@width@olf{\headwidth}
+\def\f@nch@width@ocf{\headwidth}
+\def\f@nch@width@orf{\headwidth}
+\def\f@nch@align@elh{bl}
+\def\f@nch@align@ech{bc}
+\def\f@nch@align@erh{br}
+\def\f@nch@align@olh{bl}
+\def\f@nch@align@och{bc}
+\def\f@nch@align@orh{br}
+\def\f@nch@align@elf{tl}
+\def\f@nch@align@ecf{tc}
+\def\f@nch@align@erf{tr}
+\def\f@nch@align@olf{tl}
+\def\f@nch@align@ocf{tc}
+\def\f@nch@align@orf{tr}
+\def\f@nchdrwdt@align@v@h{\def\f@nch@align@@v{b}}%
+\def\f@nchdrwdt@align@v@f{\def\f@nch@align@@v{t}}%
+\long\def\f@nchdrwdt@align#1#2\@nil#3{%
+  \f@nch@ifin{#1}{TtcbB-}{%
+    \f@nch@ifin{#1}{-}{}{\def\f@nch@align@@v{#1}}%
+    \def\@tempa{#2}%
+    \ifx\@tempa\@empty \else \def\f@nch@align@@h{#2}\fi
+  }%
+  {\def\f@nch@align@@h{#1}}%
+  \expandafter\f@nch@ifin\expandafter{\f@nch@align@@h}{lcrj}{}%
+    {\PackageError{fancyhdr}
+                  {\string#3: Illegal char `\f@nch@align@@h'\MessageBreak
+                              in alignment argument}{}}%
+}
+\newcommand{\lhead}[2][\f@nch@olh]%
+                     {\f@nch@def\f@nch@olh{#2}\f@nch@def\f@nch@elh{#1}}
+\newcommand{\chead}[2][\f@nch@och]%
+                     {\f@nch@def\f@nch@och{#2}\f@nch@def\f@nch@ech{#1}}
+\newcommand{\rhead}[2][\f@nch@orh]%
+                     {\f@nch@def\f@nch@orh{#2}\f@nch@def\f@nch@erh{#1}}
+\newcommand{\lfoot}[2][\f@nch@olf]%
+                     {\f@nch@def\f@nch@olf{#2}\f@nch@def\f@nch@elf{#1}}
+\newcommand{\cfoot}[2][\f@nch@ocf]%
+                     {\f@nch@def\f@nch@ocf{#2}\f@nch@def\f@nch@ecf{#1}}
+\newcommand{\rfoot}[2][\f@nch@orf]%
+                     {\f@nch@def\f@nch@orf{#2}\f@nch@def\f@nch@erf{#1}}
+\newlength{\f@nch@headwidth} \let\headwidth\f@nch@headwidth
+\newlength{\f@nch@offset@elh}
+\newlength{\f@nch@offset@erh}
+\newlength{\f@nch@offset@olh}
+\newlength{\f@nch@offset@orh}
+\newlength{\f@nch@offset@elf}
+\newlength{\f@nch@offset@erf}
+\newlength{\f@nch@offset@olf}
+\newlength{\f@nch@offset@orf}
+\newcommand{\headrulewidth}{0.4pt}
+\newcommand{\footrulewidth}{0pt}
+\@ifundefined{headruleskip}%
+      {\newcommand{\headruleskip}{0pt}}{}
+\@ifundefined{footruleskip}%
+      {\newcommand{\footruleskip}{.3\normalbaselineskip}}{}
+\newcommand{\plainheadrulewidth}{0pt}
+\newcommand{\plainfootrulewidth}{0pt}
+\newif\if@fancyplain \@fancyplainfalse
+\def\fancyplain#1#2{\if@fancyplain#1\else#2\fi}
+\headwidth=-123456789sp
+\let\f@nch@raggedleft\raggedleft
+\let\f@nch@raggedright\raggedright
+\let\f@nch@centering\centering
+\let\f@nch@everypar\everypar
+\ifdefined\ExplSyntaxOn
+  \ExplSyntaxOn
+  \providecommand\IfFormatAtLeastTF{\@ifl@t@r\fmtversion}
+  \IfFormatAtLeastTF{2021-06-01}{
+    \def\f@nch@saveclr@parhook #1{
+      \expandafter\let\csname f@nch@__hook~#1\expandafter\endcsname
+                      \csname __hook~#1\endcsname
+      \expandafter\let\csname f@nch@__hook_toplevel~#1\expandafter\endcsname
+                      \csname __hook_toplevel~#1\endcsname
+      \expandafter\let\csname f@nch@__hook_next~#1\expandafter\endcsname
+                      \csname __hook_next~#1\endcsname
+      \expandafter\let\csname f@nch@g__hook_#1_code_prop\expandafter\endcsname
+                      \csname g__hook_#1_code_prop\endcsname
+      \RemoveFromHook{#1}[*]
+      \ClearHookNext{#1}
+    }
+    \def\f@nch@restore@parhook #1{
+      \global\expandafter\let\csname __hook~#1\expandafter\endcsname
+                             \csname f@nch@__hook~#1\endcsname
+      \global\expandafter\let\csname __hook_toplevel~#1\expandafter\endcsname
+                             \csname f@nch@__hook_toplevel~#1\endcsname
+      \global\expandafter\let\csname __hook_next~#1\expandafter\endcsname
+                             \csname f@nch@__hook_next~#1\endcsname
+      \global\expandafter\let\csname g__hook_#1_code_prop\expandafter\endcsname
+                             \csname f@nch@g__hook_#1_code_prop\endcsname
+    }
+    \def\f@nch@resetpar{
+      \f@nch@everypar{}
+      \f@nch@saveclr@parhook{para/before}
+      \f@nch@saveclr@parhook{para/begin}
+      \f@nch@saveclr@parhook{para/end}
+      \f@nch@saveclr@parhook{para/after}
+    }
+    \def\f@nch@restorepar{
+      \f@nch@restore@parhook{para/before}
+      \f@nch@restore@parhook{para/begin}
+      \f@nch@restore@parhook{para/end}
+      \f@nch@restore@parhook{para/after}
+    }
+  }{
+    \def\f@nch@resetpar{
+      \f@nch@everypar{}
+    }
+    \def\f@nch@restorepar{}
+  }
+  \ExplSyntaxOff
+\else
+  \def\f@nch@resetpar{%
+    \f@nch@everypar{}%
+  }
+  \def\f@nch@restorepar{}
+\fi
+\newcommand\f@nch@noUppercase[2][]{#2}
+\def\f@nch@reset{\f@nch@resetpar\restorecr\endlinechar=13
+  \catcode`\\=0\catcode`\{=1\catcode`\}=2\catcode`\$=3\catcode`\&=4
+  \catcode`\#=6\catcode`\^=7\catcode`\_=8\catcode`\ =10\catcode`\@=11
+  \catcode`\:=11\catcode`\~=13\catcode`\%=14
+  \catcode0=15 %NULL
+  \catcode9=10 %TAB
+  \let\\\@normalcr \let\raggedleft\f@nch@raggedleft
+  \let\raggedright\f@nch@raggedright \let\centering\f@nch@centering
+  \def\baselinestretch{1}%
+  \hsize=\headwidth
+  \def\nouppercase##1{{%
+      \let\uppercase\relax\let\MakeUppercase\f@nch@noUppercase
+      \expandafter\let\csname MakeUppercase \endcsname\relax
+      \expandafter\def\csname MakeUppercase\space\space\space\endcsname
+                                                   [####1]####2{####2}%
+      ##1}}%
+  \@ifundefined{@normalsize} {\normalsize} % for ucthesis.cls
+   {\@normalsize}%
+  }
+\newcommand*{\fancycenter}[1][1em]{%
+  \@ifnextchar[{\f@nch@center{#1}}{\f@nch@center{#1}[3]}%
+}
+\def\f@nch@center#1[#2]#3#4#5{%
+  \def\@tempa{#4}\ifx\@tempa\@empty
+    \hbox to\linewidth{\color@begingroup{#3}\hfil {#5}\color@endgroup}%
+  \else
+    \setlength\@tempdima{#1}%
+    \setlength{\@tempdimb}{#2\@tempdima}%
+    \@tempdimc \@tempdimb \advance\@tempdimc -\@tempdima
+    \setlength\@tempskipa{\@tempdimb \@plus 1fil \@minus \@tempdimc}%
+    \@tempskipb\@tempskipa
+    \def\@tempa{#3}\ifx\@tempa\@empty
+      \addtolength\@tempskipa{\z@ \@minus \@tempdima}%
+    \fi
+    \def\@tempa{#5}\ifx\@tempa\@empty % empty right
+      \addtolength\@tempskipb{\z@ \@minus \@tempdima}%
+    \fi
+    \settowidth{\@tempdimb}{#3}%
+    \settowidth{\@tempdimc}{#5}%
+    \ifdim\@tempdimb>\@tempdimc
+      \advance\@tempdimb -\@tempdimc
+      \addtolength\@tempskipb{\@tempdimb \@minus \@tempdimb}%
+    \else
+      \advance\@tempdimc -\@tempdimb
+      \addtolength\@tempskipa{\@tempdimc \@minus \@tempdimc}%
+    \fi
+    \hbox to\linewidth{\color@begingroup{#3}\hskip \@tempskipa
+                      {#4}\hskip \@tempskipb {#5}\color@endgroup}%
+  \fi
+}
+\newcommand{\f@nch@headinit}{}
+\newcommand{\fancyheadinit}[1]{%
+  \def\f@nch@headinit{#1}%
+}
+\newcommand{\f@nch@footinit}{}
+\newcommand{\fancyfootinit}[1]{%
+  \def\f@nch@footinit{#1}%
+}
+\newcommand{\fancyhfinit}[1]{%
+  \def\f@nch@headinit{#1}%
+  \def\f@nch@footinit{#1}%
+}
+\ifdefined\NewMirroredHookPair
+  \NewMirroredHookPair{fancyhdr/before}{fancyhdr/after}
+  \NewMirroredHookPair{fancyhdr/head/begin}{fancyhdr/head/end}
+  \NewMirroredHookPair{fancyhdr/foot/begin}{fancyhdr/foot/end}
+\fi
+\newlength\f@nch@height
+\newlength\f@nch@footalignment
+\newif\iff@nch@footalign\f@nch@footalignfalse
+\newcommand{\fancyfootalign}[1]{%
+  \def\temp@a{#1}%
+  \ifx\temp@a\@empty
+    \f@nch@footalignfalse
+  \else
+    \f@nch@footaligntrue
+    \setlength\f@nch@footalignment{#1}%
+  \fi
+}
+\newcommand\fancyhdrsettoheight[2]{%
+  \expandafter\ifx\csname f@nch@#2\endcsname\fancyhdrsettoheight
+    \else\PackageError{fancyhdr}{Unknown parameter #2 in \string\fancyhdrsettoheight}{}\fi
+  \setbox\@tempboxa\hbox{{\f@nch@checkfalse\csname @#2\endcsname}}%
+  \setlength{#1}\f@nch@height
+  \setbox\@tempboxa\box\voidb@x
+}
+\let\f@nch@oddhead\fancyhdrsettoheight
+\let\f@nch@evenhead\fancyhdrsettoheight
+\let\f@nch@oddfoot\fancyhdrsettoheight
+\let\f@nch@evenfoot\fancyhdrsettoheight
+\newcommand\f@nch@vbox[2]{%
+  \setbox0\vbox{#2}%
+  \global\f@nch@height=\ht0
+  \ifdim\ht0>#1\relax
+    \iff@nch@check
+      \dimen0=#1\advance\dimen0-\ht0
+      \PackageWarning{fancyhdr}{%
+        \string#1 is too small (\the#1): \MessageBreak
+        Make it at least \the\ht0, for example:\MessageBreak
+        \string\setlength{\string#1}{\the\ht0}%
+        \iff@nch@compatViii .\MessageBreak
+        We now make it that large for the rest of the document.\MessageBreak
+        This may cause the page layout to be inconsistent, however
+        \fi
+        \ifx#1\headheight .\MessageBreak
+          You might also make \topmargin smaller:\MessageBreak
+          \string\addtolength{\string\topmargin}{\the\dimen0}%
+        \fi
+        \@gobble
+      }%
+      \iff@nch@compatViii
+        \dimen0=#1\relax
+        \global#1=\ht0\relax
+        \ht0=\dimen0 %
+      \else
+        \ht0=#1\relax
+      \fi
+    \else
+      \ht0=#1\relax
+    \fi
+  \fi
+  \box0}
+\newcommand\f@nch@head[6]{%
+  \f@nch@reset
+  \ifdefined\UseHook\UseHook{fancyhdr/before}\UseHook{fancyhdr/head/begin}\fi
+  \f@nch@headinit\relax
+  #1%
+  \hbox to\headwidth{%
+    \f@nch@vbox\headheight{%
+      \f@nch@hfbox{#2}{#3}{#4}{#6}{h}%
+      \vskip\headruleskip\relax
+      \headrule
+    }%
+  }%
+  #5%
+  \ifdefined\UseHook\UseHook{fancyhdr/head/end}\UseHook{fancyhdr/after}\fi
+  \f@nch@restorepar
+}
+\newcommand\f@nch@foot[6]{%
+  \f@nch@reset
+  \ifdefined\UseHook\UseHook{fancyhdr/before}\UseHook{fancyhdr/foot/begin}\fi
+  \f@nch@footinit\relax
+  #1%
+  \hbox to\headwidth{%
+    \f@nch@vbox\footskip{%
+      \setbox0=\vbox{\footrule}\unvbox0
+      \vskip\footruleskip
+      \f@nch@hfbox{#2}{#3}{#4}{#6}{f}%
+    \iff@nch@footalign \vskip\f@nch@footalignment \fi
+    }%
+  }%
+  #5%
+  \ifdefined\UseHook\UseHook{fancyhdr/foot/end}\UseHook{fancyhdr/after}\fi
+  \f@nch@restorepar
+}
+\newlength\f@nch@widthL
+\newlength\f@nch@widthC
+\newlength\f@nch@widthR
+\newcommand\f@nch@hfbox[5]{%
+  \setlength\f@nch@widthL{\csname f@nch@width@#4l#5\endcsname}%
+  \setlength\f@nch@widthC{\csname f@nch@width@#4c#5\endcsname}%
+  \setlength\f@nch@widthR{\csname f@nch@width@#4r#5\endcsname}%
+  \let\@tempa\f@nch@hfbox@center
+  \ifdim \dimexpr \f@nch@widthL+\f@nch@widthC+\f@nch@widthR>\headwidth
+  \else
+    \ifdim \dimexpr \f@nch@widthL+0.5\f@nch@widthC>0.5\headwidth
+      \let \@tempa\f@nch@hfbox@fit
+    \fi
+    \ifdim \dimexpr \f@nch@widthR+0.5\f@nch@widthC>0.5\headwidth
+      \let \@tempa\f@nch@hfbox@fit
+    \fi
+  \fi
+  \@tempa{#1}{#2}{#3}#4#5%
+}
+\newcommand\f@nch@hfbox@center[5]{%
+  \hbox to \headwidth{%
+    \rlap{\f@nch@parbox{#1}\f@nch@widthL{#4}l{#5}}%
+    \hfill
+    \f@nch@parbox{#2}\f@nch@widthC{#4}c{#5}%
+    \hfill
+    \llap{\f@nch@parbox{#3}\f@nch@widthR{#4}r{#5}}%
+  }%
+}
+\newcommand\f@nch@hfbox@fit[5]{%
+  \hbox to \headwidth{%
+    \f@nch@parbox{#1}\f@nch@widthL{#4}l{#5}%
+    \hfill
+    \f@nch@parbox{#2}\f@nch@widthC{#4}c{#5}%
+    \hfill
+    \f@nch@parbox{#3}\f@nch@widthR{#4}r{#5}%
+  }%
+}%
+\newcommand\f@nch@parbox[5]{%
+  \expandafter\expandafter\expandafter\f@nch@parbox@align
+                     \csname f@nch@align@#3#4#5\endcsname
+  \parbox[\f@nch@align@@v]{#2}%
+    {%
+      \f@nch@align@@pre
+      \f@nch@align@@h\leavevmode\ignorespaces#1%
+      \f@nch@align@@post
+    }%
+}
+\newcommand\f@nch@parbox@align[2]{%
+  \def\f@nch@align@@pre{}%
+  \def\f@nch@align@@post{}%
+  \csname f@nch@parbox@align@v#1\endcsname
+  \csname f@nch@parbox@align@h#2\endcsname
+}
+\def\f@nch@parbox@align@vT{\def\f@nch@align@@v{t}\def\f@nch@align@@pre{\vspace{0pt}}}
+\def\f@nch@parbox@align@vt{\def\f@nch@align@@v{t}}
+\def\f@nch@parbox@align@vc{\def\f@nch@align@@v{c}}
+\def\f@nch@parbox@align@vb{\def\f@nch@align@@v{b}}
+\def\f@nch@parbox@align@vB{\def\f@nch@align@@v{b}\def\f@nch@align@@post{\vspace{0pt}}}
+\def\f@nch@parbox@align@hl{\def\f@nch@align@@h{\raggedright}}
+\def\f@nch@parbox@align@hc{\def\f@nch@align@@h{\centering}}
+\def\f@nch@parbox@align@hr{\def\f@nch@align@@h{\raggedleft}}
+\def\f@nch@parbox@align@hj{\def\f@nch@align@@h{}}
+\@ifundefined{@chapapp}{\let\@chapapp\chaptername}{}%
+\def\f@nch@initialise{%
+  \@ifundefined{chapter}%
+   {\def\sectionmark##1{\markboth{\MakeUppercase{\ifnum \c@secnumdepth>\z@
+          \thesection\hskip 1em\relax
+        \fi ##1}}{}}%
+    \def\subsectionmark##1{\markright {\ifnum \c@secnumdepth >\@ne
+      \thesubsection\hskip 1em\relax \fi ##1}}}%
+   {\def\chaptermark##1{\markboth {\MakeUppercase{\ifnum
+        \c@secnumdepth>\m@ne \@chapapp\ \thechapter. \ \fi ##1}}{}}%
+    \def\sectionmark##1{\markright{\MakeUppercase{\ifnum \c@secnumdepth >\z@
+        \thesection. \ \fi ##1}}}%
+   }%
+  \def\headrule{{\if@fancyplain\let\headrulewidth\plainheadrulewidth\fi
+      \hrule\@height\headrulewidth\@width\headwidth
+      \vskip-\headrulewidth}}%
+  \def\footrule{{\if@fancyplain\let\footrulewidth\plainfootrulewidth\fi
+      \hrule\@width\headwidth\@height\footrulewidth}}%
+  \def\headrulewidth{0.4pt}%
+  \def\footrulewidth{0pt}%
+  \def\headruleskip{0pt}%
+  \def\footruleskip{0.3\normalbaselineskip}%
+  \fancyhf{}%
+  \if@twoside
+    \fancyhead[el,or]{\fancyplain{}{\slshape\rightmark}}%
+    \fancyhead[er,ol]{\fancyplain{}{\slshape\leftmark}}%
+  \else
+    \fancyhead[l]{\fancyplain{}{\slshape\rightmark}}%
+    \fancyhead[r]{\fancyplain{}{\slshape\leftmark}}%
+  \fi
+  \fancyfoot[c]{\rmfamily\thepage}% page number
+}
+\f@nch@initialise
+\def\ps@f@nch@fancyproto{%
+  \ifdim\headwidth<0sp
+    \global\advance\headwidth123456789sp\global\advance\headwidth\textwidth
+  \fi
+  \gdef\ps@f@nch@fancyproto{\@fancyplainfalse\ps@f@nch@fancycore}%
+  \@fancyplainfalse\ps@f@nch@fancycore
+}%
+\@namedef{f@nch@ps@f@nch@fancyproto-is-fancyhdr}{}
+\def\ps@fancy{\ps@f@nch@fancyproto}
+\@namedef{f@nch@ps@fancy-is-fancyhdr}{}
+\def\ps@fancyplain{\ps@f@nch@fancyproto \let\ps@plain\ps@plain@fancy}
+\def\ps@plain@fancy{\@fancyplaintrue\ps@f@nch@fancycore}
+\let\f@nch@ps@empty\ps@empty
+\def\ps@f@nch@fancycore{%
+  \f@nch@ps@empty
+  \def\@mkboth{\protect\markboth}%
+  \def\f@nch@oddhead{\f@nch@head\f@nch@Oolh\f@nch@olh\f@nch@och\f@nch@orh\f@nch@Oorh{o}}%
+  \def\@oddhead{%
+    \iff@nch@twoside
+      \ifodd\c@page
+        \f@nch@oddhead
+      \else
+        \@evenhead
+      \fi
+    \else
+      \f@nch@oddhead
+    \fi
+  }
+  \def\f@nch@oddfoot{\f@nch@foot\f@nch@Oolf\f@nch@olf\f@nch@ocf\f@nch@orf\f@nch@Oorf{o}}%
+  \def\@oddfoot{%
+    \iff@nch@twoside
+      \ifodd\c@page
+        \f@nch@oddfoot
+      \else
+        \@evenfoot
+      \fi
+    \else
+      \f@nch@oddfoot
+    \fi
+  }
+  \def\@evenhead{\f@nch@head\f@nch@Oelh\f@nch@elh\f@nch@ech\f@nch@erh\f@nch@Oerh{e}}%
+  \def\@evenfoot{\f@nch@foot\f@nch@Oelf\f@nch@elf\f@nch@ecf\f@nch@erf\f@nch@Oerf{e}}%
+}
+\def\f@nch@Oolh{\if@reversemargin\hss\else\relax\fi}
+\def\f@nch@Oorh{\if@reversemargin\relax\else\hss\fi}
+\let\f@nch@Oelh\f@nch@Oorh
+\let\f@nch@Oerh\f@nch@Oolh
+\let\f@nch@Oolf\f@nch@Oolh
+\let\f@nch@Oorf\f@nch@Oorh
+\let\f@nch@Oelf\f@nch@Oelh
+\let\f@nch@Oerf\f@nch@Oerh
+\def\f@nch@offsolh{\headwidth=\textwidth\advance\headwidth\f@nch@offset@olh
+                   \advance\headwidth\f@nch@offset@orh\hskip-\f@nch@offset@olh}
+\def\f@nch@offselh{\headwidth=\textwidth\advance\headwidth\f@nch@offset@elh
+                   \advance\headwidth\f@nch@offset@erh\hskip-\f@nch@offset@elh}
+\def\f@nch@offsolf{\headwidth=\textwidth\advance\headwidth\f@nch@offset@olf
+                   \advance\headwidth\f@nch@offset@orf\hskip-\f@nch@offset@olf}
+\def\f@nch@offself{\headwidth=\textwidth\advance\headwidth\f@nch@offset@elf
+                   \advance\headwidth\f@nch@offset@erf\hskip-\f@nch@offset@elf}
+\def\f@nch@setoffs{%
+  \f@nch@gbl\let\headwidth\f@nch@headwidth
+  \f@nch@gbl\def\f@nch@Oolh{\f@nch@offsolh}%
+  \f@nch@gbl\def\f@nch@Oelh{\f@nch@offselh}%
+  \f@nch@gbl\def\f@nch@Oorh{\hss}%
+  \f@nch@gbl\def\f@nch@Oerh{\hss}%
+  \f@nch@gbl\def\f@nch@Oolf{\f@nch@offsolf}%
+  \f@nch@gbl\def\f@nch@Oelf{\f@nch@offself}%
+  \f@nch@gbl\def\f@nch@Oorf{\hss}%
+  \f@nch@gbl\def\f@nch@Oerf{\hss}%
+}
+\newif\iff@nch@footnote
+\AtBeginDocument{%
+  \let\latex@makecol\@makecol
+  \def\@makecol{\ifvoid\footins\f@nch@footnotefalse\else\f@nch@footnotetrue\fi
+    \let\f@nch@topfloat\@toplist\let\f@nch@botfloat\@botlist\latex@makecol}%
+}
+\newcommand\iftopfloat[2]{\ifx\f@nch@topfloat\@empty #2\else #1\fi}%
+\newcommand\ifbotfloat[2]{\ifx\f@nch@botfloat\@empty #2\else #1\fi}%
+\newcommand\iffloatpage[2]{\if@fcolmade #1\else #2\fi}%
+\newcommand\iffootnote[2]{\iff@nch@footnote #1\else #2\fi}%
+\ifx\@temptokenb\undefined \csname newtoks\endcsname\@temptokenb\fi
+\newif\iff@nch@pagestyle@star
+\newcommand\fancypagestyle{%
+  \@ifstar{\f@nch@pagestyle@startrue\f@nch@pagestyle}%
+          {\f@nch@pagestyle@starfalse\f@nch@pagestyle}%
+}
+\newcommand\f@nch@pagestyle[1]{%
+  \@ifnextchar[{\f@nch@@pagestyle{#1}}{\f@nch@@pagestyle{#1}[f@nch@fancyproto]}%
+}
+\long\def\f@nch@@pagestyle#1[#2]#3{%
+  \@ifundefined{ps@#2}{%
+    \PackageError{fancyhdr}{\string\fancypagestyle: Unknown base page style `#2'}{}%
+  }{%
+    \@ifundefined{f@nch@ps@#2-is-fancyhdr}{%
+      \PackageError{fancyhdr}{\string\fancypagestyle: Base page style `#2' is not fancyhdr-based}{}%
+    }%
+    {%
+      \f@nch@pagestyle@setup
+      \def\temp@b{\@namedef{ps@#1}}%
+      \expandafter\temp@b\expandafter{\the\@temptokenb
+          \let\f@nch@gbl\relax\@nameuse{ps@#2}#3\relax}%
+      \@namedef{f@nch@ps@#1-is-fancyhdr}{}%
+    }%
+  }%
+}
+\newcommand\f@nch@pagestyle@setup{%
+  \iff@nch@pagestyle@star
+    \iff@nch@check\@temptokenb={\f@nch@checktrue}\else\@temptokenb={\f@nch@checkfalse}\fi
+    \@tfor\temp@a:=
+      \f@nch@olh\f@nch@och\f@nch@orh\f@nch@elh\f@nch@ech\f@nch@erh
+      \f@nch@olf\f@nch@ocf\f@nch@orf\f@nch@elf\f@nch@ecf\f@nch@erf
+      \f@nch@width@elh\f@nch@width@ech\f@nch@width@erh\f@nch@width@olh
+      \f@nch@width@och\f@nch@width@orh\f@nch@width@elf\f@nch@width@ecf
+      \f@nch@width@erf\f@nch@width@olf\f@nch@width@ocf\f@nch@width@orf
+      \f@nch@align@elh\f@nch@align@ech\f@nch@align@erh\f@nch@align@olh
+      \f@nch@align@och\f@nch@align@orh\f@nch@align@elf\f@nch@align@ecf
+      \f@nch@align@erf\f@nch@align@olf\f@nch@align@ocf\f@nch@align@orf
+      \f@nch@Oolh\f@nch@Oorh\f@nch@Oelh\f@nch@Oerh
+      \f@nch@Oolf\f@nch@Oorf\f@nch@Oelf\f@nch@Oerf
+      \f@nch@headinit\f@nch@footinit
+      \headrule\headrulewidth\footrule\footrulewidth
+    \do {%
+      \toks@=\expandafter\expandafter\expandafter{\temp@a}%
+      \toks@=\expandafter\expandafter\expandafter{%
+        \expandafter\expandafter\expandafter\def
+        \expandafter\expandafter\temp@a\expandafter{\the\toks@}}%
+      \edef\temp@b{\@temptokenb={\the\@temptokenb\the\toks@}}%
+      \temp@b
+    }%
+    \@tfor\temp@a:=
+      \f@nch@offset@olh\f@nch@offset@orh\f@nch@offset@elh\f@nch@offset@erh
+      \f@nch@offset@olf\f@nch@offset@orf\f@nch@offset@elf\f@nch@offset@erf
+    \do {%
+      \toks@=\expandafter\expandafter\expandafter{\expandafter\the\temp@a}%
+      \toks@=\expandafter\expandafter\expandafter{%
+        \expandafter\expandafter\expandafter\setlength
+        \expandafter\expandafter\temp@a\expandafter{\the\toks@}}%
+      \edef\temp@b{\@temptokenb={\the\@temptokenb\the\toks@}}%
+      \temp@b
+    }%
+  \else
+    \@temptokenb={}%
+  \fi
+}
+\newcommand\fancypagestyleassign[2]{%
+  \@ifundefined{ps@#2}{%
+    \PackageError{fancyhdr}{\string\fancypagestyleassign: Unknown page style `#2'}{}%
+    }{%
+     \expandafter\let
+       \csname ps@#1\expandafter\endcsname
+       \csname ps@#2\endcsname
+     \@ifundefined{f@nch@ps@#2-is-fancyhdr}{%
+       \expandafter\let\csname f@nch@ps@#1-is-fancyhdr\endcsname\@undefined
+     }{%
+       \@namedef{f@nch@ps@#1-is-fancyhdr}{}%
+     }%
+   }%
+}
+\fancypagestyle*{fancydefault}{\f@nch@initialise}
+\def\f@nchdrbox@topstrut{\vrule height\ht\strutbox width\z@}
+\def\f@nchdrbox@botstrut{\vrule depth\dp\strutbox width\z@}
+\def\f@nchdrbox@nostrut{\noalign{\vspace{0pt}}\let\f@nchdrbox@@crstrut\f@nchdrbox@botstrut}
+\NewDocumentCommand{\fancyhdrbox}{ O{cl} o m }{%
+\begingroup
+  \let\f@nchdrbox@@pre\f@nchdrbox@topstrut
+  \let\f@nchdrbox@@postx\f@nchdrbox@botstrut
+  \let\f@nchdrbox@@posty\relax
+  \let\f@nchdrbox@@crstrut\strut
+  \IfNoValueTF{#2}%
+    {\let\f@nchdrbox@@halignto\@empty}%
+    {\setlength\@tempdima{#2}%
+      \def\f@nchdrbox@@halignto{to\@tempdima}}%
+  \def\@tempa{#1}%
+  \ifx\@tempa\@empty
+    \f@nchdrbox@align cl\@nil{#3}%
+  \else
+    \f@nchdrbox@align #1\@nil{#3}%
+  \fi
+\endgroup
+}
+\protected\def\f@nchdrbox@cr{%
+  {\ifnum0=`}\fi\@ifstar\@f@nchdrbox@xcr\@f@nchdrbox@xcr}
+
+\def\@f@nchdrbox@xcr{%
+  \unskip\f@nchdrbox@@crstrut
+  \@ifnextchar[\@f@nchdrbox@argc{\ifnum0=`{\fi}\cr}%
+}
+
+\def\@f@nchdrbox@argc[#1]{%
+  \ifnum0=`{\fi}%
+    \ifdim #1>\z@
+      \unskip\@f@nchdrbox@xargc{#1}%
+    \else
+      \@f@nchdrbox@yargc{#1}%
+    \fi}
+
+\def\@f@nchdrbox@xargc#1{\@tempdima #1\advance\@tempdima \dp \strutbox
+   \vrule \@height\z@ \@depth\@tempdima \@width\z@ \cr}
+
+\def\@f@nchdrbox@yargc#1{\cr\noalign{\setlength\@tempdima{#1}\vskip\@tempdima}}
+\def\f@nchdrbox@T{\let\f@nchdrbox@@pre\f@nchdrbox@nostrut
+                  \f@nchdrbox@t}
+\def\f@nchdrbox@t{\def\f@nchdrbox@@v{t}\def\f@nchdrbox@@h{l}}
+\def\f@nchdrbox@c{\def\f@nchdrbox@@v{c}\def\f@nchdrbox@@h{c}}
+\def\f@nchdrbox@b{\def\f@nchdrbox@@v{b}\def\f@nchdrbox@@h{l}}
+\def\f@nchdrbox@B{\let\f@nchdrbox@@postx\relax
+                  \def\f@nchdrbox@@posty{\vspace{0pt}}%
+                  \f@nchdrbox@b}
+\long\def\f@nchdrbox@align#1#2\@nil#3{%
+  \f@nch@ifin{#1}{TtcbB}{%
+    \@nameuse{f@nchdrbox@#1}%
+    \def\@tempa{#2}%
+    \ifx\@tempa\@empty\else \def\f@nchdrbox@@h{#2}\fi
+  }%
+  {\def\f@nchdrbox@@v{c}\def\f@nchdrbox@@h{#1}}%
+  \expandafter\f@nch@ifin\expandafter{\f@nchdrbox@@h}{lcr}{}%
+  {\PackageError{fancyhdr}{\string\fancyhdrbox: Illegal char `\f@nchdrbox@@h'\MessageBreak
+                            in alignment argument}{}}%
+  \let\\\f@nchdrbox@cr
+  \setbox0=\if \f@nchdrbox@@v t\vtop
+  \else \vbox
+  \fi
+  {%
+     \ialign \f@nchdrbox@@halignto
+     \bgroup \relax
+     {\if \f@nchdrbox@@h l\hskip 1sp\else \hfil \fi
+       \ignorespaces ##\unskip
+       \if\f@nchdrbox@@h r\else \hfil \fi
+     }%
+     \tabskip\z@skip \cr
+     \f@nchdrbox@@pre
+     #3\unskip \f@nchdrbox@@postx
+     \crcr
+     \egroup
+     \f@nchdrbox@@posty
+  }%
+  \if\f@nchdrbox@@v c\@tempdima=\ht0\advance\@tempdima\dp0%
+    \ht0=0.5\@tempdima\dp0=0.5\@tempdima\fi
+  \leavevmode \box0
+}
+\@ifclassloaded{newlfm}
+{
+  \let\ps@@empty\f@nch@ps@empty
+  \AtBeginDocument{%
+    \renewcommand{\@zfancyhead}[5]{\relax\hbox to\headwidth{\f@nch@reset
+      \@zfancyvbox\headheight{\hbox
+        {\rlap{\parbox[b]{\headwidth}{\raggedright\f@nch@olh}}\hfill
+          \parbox[b]{\headwidth}{\centering\f@nch@olh}\hfill
+          \llap{\parbox[b]{\headwidth}{\raggedleft\f@nch@orh}}}%
+        \zheadrule}}\relax}%
+  }
+}
+{}
+\endinput
+%%
+%% End of file `fancyhdr.sty'.