Author

Yingyu Shan

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Preprint Aug 2026

Behavior2Trip: Towards Personalized Travel Planning via User Behavior Trajectory

A new task, Behavior-Aware Travel Planning, which infers user preferences directly from past behaviors and generates personalized travel plans and proposes B2T-Agent, a reinforcement learning-based agent that leverages user behavior trajectories, interacts with external tools for preference-aligned retrieval, and maintains an internal memory module.

Zihao Cheng, Yingyu Shan, Hongru Wang et al. · 0 citations

#natural language process... Jun 2026

Self-Evaluation Is Already There: Eliciting Latent Judge Calibration in Base LLMs with Minimal Data

Self-Evaluation Elicitation (SEE) is introduced, a method that surfaces a latent ability to predict how a judge will score its own output through a short cycle comprising a calibration-coupled reinforcement learning phase that improves the answer and predicts the judge, followed by a masked distillation phase that sharpens the prediction while leaving the answer untouched.

XiuYu Zhang, Yingyu Shan, Junfeng Fang et al. · arXiv.org · 2 citations