most citedOn the Algorithmic Bias of Aligning Large Language Models with RLHF: Preference Collapse and Matching Regularization

6 citations · 6 across the 1 of their papers we have counts for

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stat.ML2024★ 6 cited

On the Algorithmic Bias of Aligning Large Language Models with RLHF: Preference Collapse and Matching Regularization

Jiancong Xiao, Ziniu Li, Xingyu Xie +4

Accurately aligning large language models (LLMs) with human preferences is crucial for informing fair, economically sound, and statistically efficient decision-making processes. Ho…