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DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 447 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 140 -
StoryMaker: Towards Holistic Consistent Characters in Text-to-image Generation
Paper • 2409.12576 • Published • 16 -
Transformer Explainer: Interactive Learning of Text-Generative Models
Paper • 2408.04619 • Published • 175
Collections
Discover the best community collections!
Collections including paper arxiv:2505.24863
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AM-Thinking-v1: Advancing the Frontier of Reasoning at 32B Scale
Paper • 2505.08311 • Published • 19 -
Towards a Deeper Understanding of Reasoning Capabilities in Large Language Models
Paper • 2505.10543 • Published • 2 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
Learning to Reason for Factuality
Paper • 2508.05618 • Published • 7
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URSA: Understanding and Verifying Chain-of-thought Reasoning in Multimodal Mathematics
Paper • 2501.04686 • Published • 53 -
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Paper • 2501.09686 • Published • 41 -
LLaVA-o1: Let Vision Language Models Reason Step-by-Step
Paper • 2411.10440 • Published • 129 -
TheoremExplainAgent: Towards Multimodal Explanations for LLM Theorem Understanding
Paper • 2502.19400 • Published • 47
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EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 30 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 15 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
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Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 282 -
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Paper • 2506.01939 • Published • 190 -
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
Paper • 2505.24864 • Published • 146 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97
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lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 196 • 99 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 39 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
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Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 120 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 146
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Phi-4 Technical Report
Paper • 2412.08905 • Published • 123 -
Evaluating and Aligning CodeLLMs on Human Preference
Paper • 2412.05210 • Published • 48 -
Evaluating Language Models as Synthetic Data Generators
Paper • 2412.03679 • Published • 47 -
Yi-Lightning Technical Report
Paper • 2412.01253 • Published • 28
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Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 40 -
Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
Paper • 2310.08491 • Published • 57 -
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Paper • 2411.04282 • Published • 37 -
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
Paper • 2411.14432 • Published • 25
-
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Paper • 2501.12948 • Published • 447 -
Training Language Models to Self-Correct via Reinforcement Learning
Paper • 2409.12917 • Published • 140 -
StoryMaker: Towards Holistic Consistent Characters in Text-to-image Generation
Paper • 2409.12576 • Published • 16 -
Transformer Explainer: Interactive Learning of Text-Generative Models
Paper • 2408.04619 • Published • 175
-
Reflect, Retry, Reward: Self-Improving LLMs via Reinforcement Learning
Paper • 2505.24726 • Published • 282 -
Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning
Paper • 2506.01939 • Published • 190 -
ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
Paper • 2505.24864 • Published • 146 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 196 • 99 -
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Paper • 2503.09516 • Published • 39 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning
Paper • 2505.17667 • Published • 88
-
AM-Thinking-v1: Advancing the Frontier of Reasoning at 32B Scale
Paper • 2505.08311 • Published • 19 -
Towards a Deeper Understanding of Reasoning Capabilities in Large Language Models
Paper • 2505.10543 • Published • 2 -
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time
Paper • 2505.24863 • Published • 97 -
Learning to Reason for Factuality
Paper • 2508.05618 • Published • 7
-
Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model
Paper • 2503.24290 • Published • 62 -
I Have Covered All the Bases Here: Interpreting Reasoning Features in Large Language Models via Sparse Autoencoders
Paper • 2503.18878 • Published • 120 -
START: Self-taught Reasoner with Tools
Paper • 2503.04625 • Published • 113 -
DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Paper • 2503.14476 • Published • 146
-
URSA: Understanding and Verifying Chain-of-thought Reasoning in Multimodal Mathematics
Paper • 2501.04686 • Published • 53 -
Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models
Paper • 2501.09686 • Published • 41 -
LLaVA-o1: Let Vision Language Models Reason Step-by-Step
Paper • 2411.10440 • Published • 129 -
TheoremExplainAgent: Towards Multimodal Explanations for LLM Theorem Understanding
Paper • 2502.19400 • Published • 47
-
Phi-4 Technical Report
Paper • 2412.08905 • Published • 123 -
Evaluating and Aligning CodeLLMs on Human Preference
Paper • 2412.05210 • Published • 48 -
Evaluating Language Models as Synthetic Data Generators
Paper • 2412.03679 • Published • 47 -
Yi-Lightning Technical Report
Paper • 2412.01253 • Published • 28
-
EVA-CLIP-18B: Scaling CLIP to 18 Billion Parameters
Paper • 2402.04252 • Published • 30 -
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Paper • 2402.03749 • Published • 15 -
ScreenAI: A Vision-Language Model for UI and Infographics Understanding
Paper • 2402.04615 • Published • 44 -
EfficientViT-SAM: Accelerated Segment Anything Model Without Performance Loss
Paper • 2402.05008 • Published • 23
-
Contrastive Decoding Improves Reasoning in Large Language Models
Paper • 2309.09117 • Published • 40 -
Prometheus: Inducing Fine-grained Evaluation Capability in Language Models
Paper • 2310.08491 • Published • 57 -
Language Models are Hidden Reasoners: Unlocking Latent Reasoning Capabilities via Self-Rewarding
Paper • 2411.04282 • Published • 37 -
Insight-V: Exploring Long-Chain Visual Reasoning with Multimodal Large Language Models
Paper • 2411.14432 • Published • 25