Author

SeYoung Yun

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#machine learning Preprint Sep 2026

Eliciting Weak-to-Strong Generalization with On-Policy Reverse Distillation

Weak-to-strong generalization asks whether stronger models can learn from weaker supervisors and surpass them. This question is particularly important for successive model generations and multi-domain consolidation, where repeating frontier-scale post-training from scratch can be prohibitively expensive. Yet convention...

Youngrok Park, Sangmin Bae, Hojung Jung et al. · 0 citations

#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