Rui Wu, Ruixiang Tang

When Reward Hacking Rebounds: Understanding and Mitigating It with Representation-Level Signals

arXiv:2604.01476v1 Announce Type: new Abstract: Reinforcement learning for LLMs is vulnerable to reward hacking, where models exploit shortcuts to maximize reward without solving the intended …