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Boryeong Cho

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#machine learning Preprint Aug 2026

PLC-DPO: Posterior Label Correction in Noisy and Ambiguous Preference Optimization

PLC-DPO is proposed to robustly optimize preferences by routing each pair's training signal as a clean, flip, or tie case, which reframes noisy preference learning as actively correcting supervision direction and strength rather than merely filtering suspicious examples.

Boryeong Cho, Sumyeong Ahn, SeYoung Yun · 0 citations