2 papers
cs.CL2025
P-Aligner: Enabling Pre-Alignment of Language Models via Principled Instruction Synthesis
Feifan Song, Bofei Gao, Yifan Song +6
Large Language Models (LLMs) are expected to produce safe, helpful, and honest content during interaction with human users, but they frequently fail to align with such values when…
cs.CL2025
Well Begun is Half Done: Low-resource Preference Alignment by Weak-to-Strong Decoding
Feifan Song, Shaohang Wei, Wen Luo +4
Large Language Models (LLMs) require alignment with human preferences to avoid generating offensive, false, or meaningless content. Recently, low-resource methods for LLM alignment…