Author

Mo Zhu

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#machine learning Preprint Sep 2026

Revisiting On-policy Adversarial Black-Box Distillation: Calibrating Groupwise Reward Geometry for Effective Advantage Construction

Black-box distillation is a practical route for transferring capabilities from API-accessible large language models that expose only text outputs into smaller student models. Recent on-policy adversarial methods such as GAD improve over SeqKD by forming an adversarial loop between a critic and a student, where the crit...

Xiao Cui, Mo Zhu, Yu-Lei Qin et al. · 1 citation

Aug 2026

Flexible Multi-Level Optimal Transport for Universal Cross-Tokenizer Knowledge Distillation on LLMs and Beyond.

Knowledge distillation (KD) has become a prevalent technique for compressing large language models (LLMs). Existing KD methods are constrained by the need for identical tokenizers (i.e., vocabularies) between teacher and student models, as they assume a consistent semantic correspondence across logit dimensions, limiti...

Xiao Cui, Mo Zhu, Yu-Lei Qin et al. · IEEE Transactions on Pattern... · 0 citations