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Collections including paper arxiv:2505.24864

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 28
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

Reinforcement learning

Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning

Paper • 2407.20798 • Published Jul 30, 2024 • 24
Offline Reinforcement Learning for LLM Multi-Step Reasoning

Paper • 2412.16145 • Published Dec 20, 2024 • 38
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models

Paper • 2501.03262 • Published Jan 4 • 102
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Paper • 2502.18449 • Published Feb 25 • 75

Will It Still Be True Tomorrow? Multilingual Evergreen Question Classification to Improve Trustworthy QA

Paper • 2505.21115 • Published May 27 • 139
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 184
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138

Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 274
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 184
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97

Reinforcement-Learning

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 4

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 184
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138
The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models

Paper • 2505.22617 • Published May 28 • 130

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138
ComfyUI-Copilot: An Intelligent Assistant for Automated Workflow Development

Paper • 2506.05010 • Published Jun 5 • 79
SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training

Paper • 2506.05301 • Published Jun 5 • 56
LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning

Paper • 2505.16933 • Published May 22 • 34

MLLM Reasoning, Rewarding, and Understanding

Papers on the reasoning, rewarding, and understanding of the MLLMs and LLMs

Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 274
SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis

Paper • 2506.02096 • Published Jun 2 • 52
OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation

Paper • 2506.02397 • Published Jun 3 • 35
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138

s3: You Don't Need That Much Data to Train a Search Agent via RL

Paper • 2505.14146 • Published May 20 • 18
Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI

Paper • 2505.19443 • Published May 26 • 15
ARM: Adaptive Reasoning Model

Paper • 2505.20258 • Published May 26 • 45
Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles

Paper • 2505.19914 • Published May 26 • 43

EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters

Paper • 2402.04252 • Published Feb 6, 2024 • 28
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models

Paper • 2402.03749 • Published Feb 6, 2024 • 14
ScreenAI: A Vision-Language Model for UI and Infographics Understanding

Paper • 2402.04615 • Published Feb 7, 2024 • 44
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss

Paper • 2402.05008 • Published Feb 7, 2024 • 23

RL+reason model

RL + Transformer = A General-Purpose Problem Solver

Paper • 2501.14176 • Published Jan 24 • 28
Towards General-Purpose Model-Free Reinforcement Learning

Paper • 2501.16142 • Published Jan 27 • 30
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Paper • 2501.17161 • Published Jan 28 • 123
MaxInfoRL: Boosting exploration in reinforcement learning through information gain maximization

Paper • 2412.12098 • Published Dec 16, 2024 • 4

Reinforcement learning

Diffusion Augmented Agents: A Framework for Efficient Exploration and Transfer Learning

Paper • 2407.20798 • Published Jul 30, 2024 • 24
Offline Reinforcement Learning for LLM Multi-Step Reasoning

Paper • 2412.16145 • Published Dec 20, 2024 • 38
REINFORCE++: A Simple and Efficient Approach for Aligning Large Language Models

Paper • 2501.03262 • Published Jan 4 • 102
SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Paper • 2502.18449 • Published Feb 25 • 75

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 184
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138
The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models

Paper • 2505.22617 • Published May 28 • 130

Will It Still Be True Tomorrow? Multilingual Evergreen Question Classification to Improve Trustworthy QA

Paper • 2505.21115 • Published May 27 • 139
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 184
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138
ComfyUI-Copilot: An Intelligent Assistant for Automated Workflow Development

Paper • 2506.05010 • Published Jun 5 • 79
SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training

Paper • 2506.05301 • Published Jun 5 • 56
LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning

Paper • 2505.16933 • Published May 22 • 34

Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 274
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning

Paper • 2506.01939 • Published Jun 2 • 184
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97

MLLM Reasoning, Rewarding, and Understanding

Papers on the reasoning, rewarding, and understanding of the MLLMs and LLMs

Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning

Paper • 2505.24726 • Published May 30 • 274
SynthRL: Scaling Visual Reasoning with Verifiable Data Synthesis

Paper • 2506.02096 • Published Jun 2 • 52
OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation

Paper • 2506.02397 • Published Jun 3 • 35
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138

Reinforcement-Learning

ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

Paper • 2505.24864 • Published May 30 • 138

s3: You Don't Need That Much Data to Train a Search Agent via RL

Paper • 2505.14146 • Published May 20 • 18
Vibe Coding vs. Agentic Coding: Fundamentals and Practical Implications of Agentic AI

Paper • 2505.19443 • Published May 26 • 15
ARM: Adaptive Reasoning Model

Paper • 2505.20258 • Published May 26 • 45
Enigmata: Scaling Logical Reasoning in Large Language Models with Synthetic Verifiable Puzzles

Paper • 2505.19914 • Published May 26 • 43

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