SparseRM: A Lightweight Preference Modeling with Sparse Autoencoder

Dengcan Liu, Jiahao Li, Zheren Fu +4

Reward models (RMs) are a core component in the post-training of large language models (LLMs), serving as proxies for human preference evaluation and guiding model alignment. Howev…