Author

Minghui Liu

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#artificial intelligence Preprint Sep 2026

Ladders of Thought: A Self-Evolving Curriculum of Progressively Simplified Reasoning Traces

Large language models (LLMs) excel at reasoning when scaled to hundreds of billions of parameters, but small- and mid-scale models remain brittle reasoners even with knowledge distillation (KD). We present Ladders-of-Thought (LoT), a framework that improves reasoning by combining progressive question rewrites with a se...

Ming-Hui Liu, Thomas Magelinski, De-Hao Yuan et al. · 0 citations

#machine learning Review Sep 2026

When AI Reviews Train AI Reviewers: Scientific-Judgment Collapse and Mitigation

Large language models (LLMs) increasingly participate in scientific evaluation, both as automated reviewers and as assistants to human reviewers. As model-generated reviews enter public data and future training corpora, AI peer review can become recursive: later reviewers learn from judgments produced by earlier models...

Sy-Tuyen Ho, Ming-Hui Liu, Fu-Rong Huang · 0 citations

Jul 2026

β-OPSD: Deriving with Policy Optimization, Training with Self-Distillation

This work introduces $\beta$-OPSD and derives its optimal policy as a geometric interpolation between the reference policy and the privileged teacher, and provides a principled route from self-distillation to policy optimization and back without sacrificing the efficiency that makes OPSD practical.

Jiawei Xu, Ming-Hui Liu, Juzheng Zhang et al. · arXiv.org · 1 citation