2 citations · 4 across the 2 of their papers we have counts for
2 papers
cs.CL2023★ 2 cited
Everyone Deserves A Reward: Learning Customized Human Preferences
Pengyu Cheng, Jiawen Xie, Ke Bai +2
Reward models (RMs) are essential for aligning large language models (LLMs) with human preferences to improve interaction quality. However, the real world is pluralistic, which lea…
cs.CL2023★ 2 cited
Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling
Rui Wang, Pengyu Cheng, Ricardo Henao
Pretrained language models (PLMs), such as GPT2, have achieved remarkable empirical performance in text generation tasks. However, pretrained on large-scale natural language corpor…