Author

Rui-Qi Liu

3 papers indexed here

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Preprint Aug 2026

ReOrder-OPD:Reliability-Aware Prompt Ordering for On-Policy Distillation

On-policy distillation (OPD) applies token-level teacher supervision to student-generated trajectories, but this supervision is not always reliable. Existing methods use local confidence or teacher-student agreement to weight, filter, or truncate the sampled trajectory. These signals do not directly determine whether t...

Ximo Zhu, Rui-Qi Liu, Rong Wang et al. · 3 citations

#machine learning Preprint Sep 2026

Nonparametric Variance-Penalized Actor-Critic: Statistical Inference for Risk-Sensitive Reinforcement Learning

Variance penalization is a principled approach to risk-sensitive reinforcement learning (RL) that explicitly trades expected return for policy stability. Existing methods require a dedicated second critic to estimate return variance online, adding architectural complexity and compounding estimation error during learnin...

Saunak Kumar Panda, Tong Li, Yi-Sha Xiang et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Data-free On-policy Distillation

On-policy distillation (OPD) has become a standard component of frontier post-training pipelines, yet how much its training data actually contributes has gone largely unexamined. On the two teacher--student pairings most common in practice, we find OPD almost indifferent to its data: eight prompts already match a 17k-p...

Gengsheng Li, Mao Zheng, Ming-Yang Song et al. · 0 citations