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Qi-Yong Zhong

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Preprint Aug 2026

RePolicy: Reinforcement Learning for Safety-Policy Invocation in Agent Safeguards

Safeguarding language model agents requires assessing complete execution trajectories under context-dependent safety policies. Existing policy-aware safeguards mainly rely on prompting or supervised fine-tuning, limiting their ability to adapt to unseen trajectories and changing policy contexts. We propose RePolicy, an...

Hou-Cheng Jiang, Bo-Xuan Zhang, Qi-Yong Zhong et al. · 0 citations
#natural language process... Preprint Sep 2026

MAS-OPD: On-Policy Distillation for Multi-agent Systems

MAS-OPD is presented, where Role-Advantage Specialization defines the role advantage as the difference between the teacher signals under target and non-target role conditions, and Privileged Attribution for Coordination attributes an interaction conflict to its source and supplies it to the teacher alone as privileged...

Qi-Yong Zhong, Mao Zheng, Ming-Yang Song 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
Jul 2026

EasyOPD: An Easy-to-use On-Policy Distillation Framework for Large Language Models

Experiments on reasoning, code-generation, scientific-knowledge, scientific-knowledge, and tool-use benchmarks show that these implementations can be executed through the same verl-based backend while retaining their method-specific objectives and task-dependent performance profiles.

Jie Sun, Mao Zheng, Mingyang Song et al. · 0 citations

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