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AlignDiff: Exploiting Model-Intrinsic Information for Better Preference Data Selection

This story is from 2026-09-09. It is preserved in the archive; the latest stories are on the live feed.

arXiv:2609.05899v1 Announce Type: new Abstract: Aligning large language models with human preferences remains a challenge, primarily due to the critical role of preference data quality in effective alignment. Existing datasets are frequently plagued by inherent noise and distribution shifts, which…

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  1. 2026-09-09 04:00 · arXiv cs.CL
    AlignDiff: Exploiting Model-Intrinsic Information for Better Preference Data Selection

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