Author

Ruihang Chu

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#machine learning May 2026

DiffusionOPD: A Unified Perspective of On-Policy Distillation in Diffusion Models

Theoretically, the OPD framework is lifted from discrete tokens to continuous-state Markov processes, deriving a closed-form per-step KL objective that unifies both stochastic SDE and deterministic ODE refinement via mean-matching, which provides lower variance and better generality compared to conventional PPO-style p...

Quanhao Li, Jun-Qiu Yu, Kai-Xun Jiang et al. · arXiv.org · 34 citations · ⚡10

#machine learning Preprint Jan 2026

X-Coder: Advancing Competitive Programming with Synthetic Tasks, Solutions, and Tests

This paper examines whether synthetic training artifacts can support the complete SFT-to-RL cycle for competitive programming, and synthesizes tasks, verified solutions, and reliable test cases that serve as reward signals for reinforcement learning.

Jie Wu, Haoling Li, Xin Zhang et al. · 1 citation