Fu-Chieh Chang

RL-STaR: Theoretical Analysis of Reinforcement Learning Frameworks for Self-Taught Reasoner

This work provides a theoretical framework for understanding the effectiveness of reinforcement learning on CoT reasoning and STaR, and bridges empirical findings with theoretical insights, advancing reinforcement learning approaches for reasoning in LLMs.