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Collections including paper arxiv:2508.08221

PotentialApplication

Let LLMs Break Free from Overthinking via Self-Braking Tuning

Paper • 2505.14604 • Published May 20 • 23
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios

Paper • 2505.16944 • Published May 22 • 8
Training Step-Level Reasoning Verifiers with Formal Verification Tools

Paper • 2505.15960 • Published May 21 • 7
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning

Paper • 2505.15134 • Published May 21 • 6

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49

How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models

Paper • 2509.19371 • Published Sep 19
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free

Paper • 2505.06708 • Published May 10 • 6
Selective Attention: Enhancing Transformer through Principled Context Control

Paper • 2411.12892 • Published Nov 19, 2024
A Survey of Reinforcement Learning for Large Reasoning Models

Paper • 2509.08827 • Published Sep 10 • 189

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49

Additional for LLMs

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49
Don't Overthink It: A Survey of Efficient R1-style Large Reasoning Models

Paper • 2508.02120 • Published Aug 4 • 19
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers

Paper • 2506.23918 • Published Jun 30 • 89
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey

Paper • 2509.02547 • Published Sep 2 • 225

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49
Reinforcement Learning for Reasoning in Large Language Models with One Training Example

Paper • 2504.20571 • Published Apr 29 • 98
RLPR: Extrapolating RLVR to General Domains without Verifiers

Paper • 2506.18254 • Published Jun 23 • 31

Large Reasoning Models Learn Better Alignment from Flawed Thinking

Paper • 2510.00938 • Published Oct 1 • 58
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT

Paper • 2509.19284 • Published Sep 23 • 22
Learning to Reason as Action Abstractions with Scalable Mid-Training RL

Paper • 2509.25810 • Published Sep 30 • 5
Agent Learning via Early Experience

Paper • 2510.08558 • Published Oct 9 • 266

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49
What matters when building vision-language models?

Paper • 2405.02246 • Published May 3, 2024 • 103

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 518 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 88

PotentialApplication

Let LLMs Break Free from Overthinking via Self-Braking Tuning

Paper • 2505.14604 • Published May 20 • 23
AGENTIF: Benchmarking Instruction Following of Large Language Models in Agentic Scenarios

Paper • 2505.16944 • Published May 22 • 8
Training Step-Level Reasoning Verifiers with Formal Verification Tools

Paper • 2505.15960 • Published May 21 • 7
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning

Paper • 2505.15134 • Published May 21 • 6

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49
Reinforcement Learning for Reasoning in Large Language Models with One Training Example

Paper • 2504.20571 • Published Apr 29 • 98
RLPR: Extrapolating RLVR to General Domains without Verifiers

Paper • 2506.18254 • Published Jun 23 • 31

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49

Large Reasoning Models Learn Better Alignment from Flawed Thinking

Paper • 2510.00938 • Published Oct 1 • 58
What Characterizes Effective Reasoning? Revisiting Length, Review, and Structure of CoT

Paper • 2509.19284 • Published Sep 23 • 22
Learning to Reason as Action Abstractions with Scalable Mid-Training RL

Paper • 2509.25810 • Published Sep 30 • 5
Agent Learning via Early Experience

Paper • 2510.08558 • Published Oct 9 • 266

How to inject knowledge efficiently? Knowledge Infusion Scaling Law for Pre-training Large Language Models

Paper • 2509.19371 • Published Sep 19
Gated Attention for Large Language Models: Non-linearity, Sparsity, and Attention-Sink-Free

Paper • 2505.06708 • Published May 10 • 6
Selective Attention: Enhancing Transformer through Principled Context Control

Paper • 2411.12892 • Published Nov 19, 2024
A Survey of Reinforcement Learning for Large Reasoning Models

Paper • 2509.08827 • Published Sep 10 • 189

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49
What matters when building vision-language models?

Paper • 2405.02246 • Published May 3, 2024 • 103

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49

Additional for LLMs

Part I: Tricks or Traps? A Deep Dive into RL for LLM Reasoning

Paper • 2508.08221 • Published Aug 11 • 49
Don't Overthink It: A Survey of Efficient R1-style Large Reasoning Models

Paper • 2508.02120 • Published Aug 4 • 19
Thinking with Images for Multimodal Reasoning: Foundations, Methods, and Future Frontiers

Paper • 2506.23918 • Published Jun 30 • 89
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey

Paper • 2509.02547 • Published Sep 2 • 225

lusxvr/nanoVLM-222M

Image-Text-to-Text • 0.2B • Updated May 8 • 518 • 98
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Paper • 2503.09516 • Published Mar 12 • 36
AlphaOne: Reasoning Models Thinking Slow and Fast at Test Time

Paper • 2505.24863 • Published May 30 • 97
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning

Paper • 2505.17667 • Published May 23 • 88

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