CoT-Space: A Theoretical Framework for Internal Slow-Thinking via Reinforcement Learning 事件

CoT-Space: A Theoretical Framework for Internal Slow-Thinking via Reinforcement Learning arXiv:2509.04027v3 Announce Type: replace-cross Abstract: Test-time scaling, primarily manifested through multi-step Chain-of-Thought (CoT) reasoning via Reinforcement Learning (RL), has emerged as a pivotal paradigm for enhancing the reasoning capabilities of Large Language Models (LLMs). However, a significant theoretical gap persists: traditional token-level analysis fails to capture the macroscopic dyna