Reasoning or Pattern Exploitation? Mechanistic Insights from RL-Trained Language Models
arXiv:2610.39182v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly described as acquiring "reasoning" skills after reinforcement learning with verifiable rewards. However, whether these gains reflect genuine reasoning or more superficial adaptations remains underexplored. In this work, we probe LLMs trained in a finite and exhaustively analyzable logical domain, namely Tic-Tac-Toe, and trace how internal representations evolve across reinforcement learning (RL) with G…