Models before and after RLHF are released to facilitate reproduction of the
Energy Loss Phenomenon introduced in [1], which provides a novel perspective on mitigating reward hacking in RLHF. The corresponding implementation is available at
Energy-Loss-Phenomenon (Github).
[1] Y. Miao, S. Zhang, L. Ding, Y. Zhang, L. Zhang, and D. Tao. The Energy Loss Phenomenon in RLHF: A New Perspective on Mitigating Reward Hacking. In Proceedings of the 42nd International Conference on Machine Learning (ICML 2025).
1@inproceedings{miao2025the,
2title={The Energy Loss Phenomenon in {RLHF}: A New Perspective on Mitigating Reward Hacking},
3author={Yuchun Miao and Sen Zhang and Liang Ding and Yuqi Zhang and Lefei Zhang and Dacheng Tao},
4booktitle={Forty-second International Conference on Machine Learning},
5year={2025},
6url={https://openreview.net/forum?id=82A81az3V5}
7}
