Yulin Peng — accepted AI-conference papers

2026

PSPO: Prompt-Level Prioritization and Experience-Weighted Smoothing for Efficient Policy Optimization

Xinxin Zhu, Ying He, Haowen Hou, Ruichong Zhang, Nianbo Zeng, Yulin Peng +2

AAAI 2026technical

Reinforcement Fine-tuning (RFT) methods such as Group Relative Policy Optimization (GRPO) have demonstrated strong capabilities in aligning Large Language Models with human preferences. However, these approaches often suffer from limited data efficiency, necessitating extensive on-policy rollouts to

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2026

Predictive Local Planning with Multi-Step Reward and Q-Value Forecasting

Yuhan Du, Yuxiang Cui, Yulin Peng, Yiyuan Pan, Tianhao Cai, Yue Wang +1

ICRA 2026poster

Planning in dynamic environments often relies on explicit future observation prediction or value-based estimation, both of which can be brittle or hard to generalize in uncertain settings. We propose a novel model-based reinforcement learning framework that performs trajectory rollout and optimizati…

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