Jun-Shan Zhang

Adversarial Reward Auditing for Active Detection and Mitigation of Reward Hacking

Experiments demonstrate that ARA achieves the best alignment-utility tradeoff among all baselines: reducing sycophancy to near-SFT levels while improving helpfulness, decreasing verbosity while achieving the highest ROUGE-L, and suppressing code gaming while improving Pass@1.