3 papers
cs.CL2024
Self-playing Adversarial Language Game Enhances LLM Reasoning
Pengyu Cheng, Tianhao Hu, Han Xu +6
We explore the potential of self-play training for large language models (LLMs) in a two-player adversarial language game called Adversarial Taboo. In this game, an attacker and a…
cs.AI2023
On Diversified Preferences of Large Language Model Alignment
Dun Zeng, Yong Dai, Pengyu Cheng +5
Aligning large language models (LLMs) with human preferences has been recognized as the key to improving LLMs' interaction quality. However, in this pluralistic world, human prefer…
cs.CL2023
Adversarial Preference Optimization: Enhancing Your Alignment via RM-LLM Game
Pengyu Cheng, Yifan Yang, Jian Li +5
Human preference alignment is essential to improve the interaction quality of large language models (LLMs). Existing alignment methods depend on manually annotated preference data…