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SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 125 -
Understanding R1-Zero-Like Training: A Critical Perspective
Paper • 2503.20783 • Published • 59 -
Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning
Paper • 2508.08221 • Published • 50 -
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Paper • 1910.02054 • Published • 11
Collections
Discover the best community collections!
Collections including paper arxiv:2508.08221
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How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models
Paper • 2509.19371 • Published -
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
Paper • 2505.06708 • Published • 11 -
Selective Attention: Enhancing Transformer through Principled Context Control
Paper • 2411.12892 • Published -
A Survey of Reinforcement Learning for Large Reasoning Models
Paper • 2509.08827 • Published • 193
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Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning
Paper • 2508.08221 • Published • 50 -
Don't Overthink It: A Survey of Efficient R1-style Large Reasoning Models
Paper • 2508.02120 • Published • 20 -
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Paper • 2506.23918 • Published • 90 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 238
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Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning
Paper • 2508.08221 • Published • 50 -
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Paper • 2504.20571 • Published • 98 -
RLPR: Extrapolating RLVR to General Domains without Verifiers
Paper • 2506.18254 • Published • 33
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Large Reasoning Models Learn Better Alignment from Flawed Thinking
Paper • 2510.00938 • Published • 60 -
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Paper • 2509.19284 • Published • 23 -
Learning to Reason as Action Abstractions with Scalable Mid-Training RL
Paper • 2509.25810 • Published • 6 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 277
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lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 225 • 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
-
SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training
Paper • 2501.17161 • Published • 125 -
Understanding R1-Zero-Like Training: A Critical Perspective
Paper • 2503.20783 • Published • 59 -
Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning
Paper • 2508.08221 • Published • 50 -
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models
Paper • 1910.02054 • Published • 11
-
Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning
Paper • 2508.08221 • Published • 50 -
Reinforcement Learning for Reasoning in Large Language Models with One Training Example
Paper • 2504.20571 • Published • 98 -
RLPR: Extrapolating RLVR to General Domains without Verifiers
Paper • 2506.18254 • Published • 33
-
Large Reasoning Models Learn Better Alignment from Flawed Thinking
Paper • 2510.00938 • Published • 60 -
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT
Paper • 2509.19284 • Published • 23 -
Learning to Reason as Action Abstractions with Scalable Mid-Training RL
Paper • 2509.25810 • Published • 6 -
Agent Learning via Early Experience
Paper • 2510.08558 • Published • 277
-
How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models
Paper • 2509.19371 • Published -
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free
Paper • 2505.06708 • Published • 11 -
Selective Attention: Enhancing Transformer through Principled Context Control
Paper • 2411.12892 • Published -
A Survey of Reinforcement Learning for Large Reasoning Models
Paper • 2509.08827 • Published • 193
-
Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning
Paper • 2508.08221 • Published • 50 -
Don't Overthink It: A Survey of Efficient R1-style Large Reasoning Models
Paper • 2508.02120 • Published • 20 -
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers
Paper • 2506.23918 • Published • 90 -
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Paper • 2509.02547 • Published • 238
-
lusxvr/nanoVLM-222M
Image-Text-to-Text • 0.2B • Updated • 225 • 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