-
Continuous Latent Diffusion Language Model
Paper • 2605.06548 • Published • 88 -
Scaling Latent Reasoning via Looped Language Models
Paper • 2510.25741 • Published • 241 -
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
Paper • 2502.05171 • Published • 165 -
Pretraining Language Models to Ponder in Continuous Space
Paper • 2505.20674 • Published • 3
Collections
Discover the best community collections!
Collections including paper arxiv:2608.31036
-
What Matters in Transformers? Not All Attention is Needed
Paper • 2406.15786 • Published • 32 -
Breaking the Memory Barrier: Near Infinite Batch Size Scaling for Contrastive Loss
Paper • 2410.17243 • Published • 93 -
Forgetting Transformer: Softmax Attention with a Forget Gate
Paper • 2503.02130 • Published • 32 -
Transformers without Normalization
Paper • 2503.10622 • Published • 171
-
Normalized Low-Rank Adaptation
Paper • 2608.31036 • Published • 57 -
GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling
Paper • 2604.18556 • Published • 24 -
Model Compression with Exact Budget Constraints via Riemannian Manifolds
Paper • 2605.00649 • Published • 12
-
Normalized Low-Rank Adaptation
Paper • 2608.31036 • Published • 57 -
Each Reward to Its Relevant Tokens: Reward-Specific Token-Level Credit Assignment for Multi-Reward RL
Paper • 2610.21439 • Published • 44 -
APT: Feedback-Driven Agentic Post-Training for Text-to-Image Generation
Paper • 2610.18097 • Published • 31 -
Correction Training for Diffusion Models
Paper • 2610.14136 • Published • 50
-
Why Fine-Tuning Encourages Hallucinations and How to Fix It
Paper • 2604.15574 • Published • 25 -
Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation
Paper • 2604.24763 • Published • 70 -
Programming with Data: Test-Driven Data Engineering for Self-Improving LLMs from Raw Corpora
Paper • 2604.24819 • Published • 90 -
GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
Paper • 2604.26752 • Published • 116
-
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 26 -
What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective
Paper • 2410.23743 • Published • 64 -
Direct Preference Optimization Using Sparse Feature-Level Constraints
Paper • 2411.07618 • Published • 17 -
Transformer^2: Self-adaptive LLMs
Paper • 2501.06252 • Published • 55
-
Continuous Latent Diffusion Language Model
Paper • 2605.06548 • Published • 88 -
Scaling Latent Reasoning via Looped Language Models
Paper • 2510.25741 • Published • 241 -
Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach
Paper • 2502.05171 • Published • 165 -
Pretraining Language Models to Ponder in Continuous Space
Paper • 2505.20674 • Published • 3
-
Normalized Low-Rank Adaptation
Paper • 2608.31036 • Published • 57 -
GSQ: Highly-Accurate Low-Precision Scalar Quantization for LLMs via Gumbel-Softmax Sampling
Paper • 2604.18556 • Published • 24 -
Model Compression with Exact Budget Constraints via Riemannian Manifolds
Paper • 2605.00649 • Published • 12
-
Normalized Low-Rank Adaptation
Paper • 2608.31036 • Published • 57 -
Each Reward to Its Relevant Tokens: Reward-Specific Token-Level Credit Assignment for Multi-Reward RL
Paper • 2610.21439 • Published • 44 -
APT: Feedback-Driven Agentic Post-Training for Text-to-Image Generation
Paper • 2610.18097 • Published • 31 -
Correction Training for Diffusion Models
Paper • 2610.14136 • Published • 50
-
Why Fine-Tuning Encourages Hallucinations and How to Fix It
Paper • 2604.15574 • Published • 25 -
Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation
Paper • 2604.24763 • Published • 70 -
Programming with Data: Test-Driven Data Engineering for Self-Improving LLMs from Raw Corpora
Paper • 2604.24819 • Published • 90 -
GLM-5V-Turbo: Toward a Native Foundation Model for Multimodal Agents
Paper • 2604.26752 • Published • 116
-
What Matters in Transformers? Not All Attention is Needed
Paper • 2406.15786 • Published • 32 -
Breaking the Memory Barrier: Near Infinite Batch Size Scaling for Contrastive Loss
Paper • 2410.17243 • Published • 93 -
Forgetting Transformer: Softmax Attention with a Forget Gate
Paper • 2503.02130 • Published • 32 -
Transformers without Normalization
Paper • 2503.10622 • Published • 171
-
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Paper • 2402.17193 • Published • 26 -
What Happened in LLMs Layers when Trained for Fast vs. Slow Thinking: A Gradient Perspective
Paper • 2410.23743 • Published • 64 -
Direct Preference Optimization Using Sparse Feature-Level Constraints
Paper • 2411.07618 • Published • 17 -
Transformer^2: Self-adaptive LLMs
Paper • 2501.06252 • Published • 55