Author

Kang Peng

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#natural language process... Preprint Aug 2026

Write, Execute, Refine: From Skill Followers to Skill Optimizers via Reinforcement Learning from Execution Feedback

Expert-written natural language skills can improve tool-using agents, yet agent-authored skills perform 8-11 points worse than using no skill. This gap suggests that following procedural guidance and improving it from execution evidence are distinct capabilities. Inference time loops can repair skills but do not improv...

Kang Peng, Zhi-Wei Zhang, Yichen Zhang et al. · 1 citation

#artificial intelligence Preprint Sep 2026

Verify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation

Teacher-Gated On-Policy Distillation is introduced, built on the principle that teacher reliability should be verified at the prompt level before dense supervision is admitted, and outperforms Vanilla OPD in all six single-domain settings and achieves higher seven-benchmark averages at both scales under multi-domain tr...

Zhi-Wei Zhang, Zechen Sun, Fei Zhao et al. · 6 citations

#artificial intelligence Preprint Aug 2026

Learning to Allocate Incentives for Incentivized Advertising via Offline Model-Based Reinforcement Learning

An offline model-based RL framework for cost-controllable sequential incentive allocation is developed and an independent counterfactual scorer evaluates each learned policy on held-out logs, enabling pre-launch selection without costly online exposure.

Zi-Lin Zhao, Han Yang, Tian-Pei Yang et al. · 0 citations