Author

Yi-Ming Zhu

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#artificial intelligence Preprint Sep 2026

Beyond Compression: Diagnosing How Post-Training Changes Mathematical Reasoning

Post-training is central to mathematical reasoning in modern large language models (LLMs), but endpoint pass@1 alone underidentifies what has changed. Gains may reflect newly reachable solutions, cheaper sampling of latent solutions, surface robustness, or memorisation. We compare three post-training paths under a comm...

Hong-Yang Li, Yi-Ming Zhu, Xiao Li et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Solving Without Stopping: On-Policy Distillation at Small Scale

On-policy distillation, where a student learns from a stronger teacher's feedback on its own outputs, is a common way to pass reasoning to smaller models. We analyze what it transfers at small scale, distilling Qwen3-8B into Qwen3 4B, 1.7B and 0.6B students, in thinking mode (reason at length, then end the reasoning an...

Hong-Yang Li, Yi-Ming Zhu, Xiao Li et al. · 1 citation