Author

Lin-Yi Ding

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#natural language process... Preprint Sep 2026

Learning from Think-Mode Advantage via On-Policy Distillation

Explicit intermediate reasoning gives large language models (LLMs) a stronger problem-solving mode. We study learning from this think-mode advantage via on-policy distillation (OPD). OPD preserves student-generated trajectories and provides dense token-level teacher targets at student-visited prefixes. Privileged reaso...

Wan-Qi Ren, Jian-Xiang Wang, Dan-Xuan Liu et al. · 0 citations

#artificial intelligence Preprint Jul 2026

APeB: Benchmarking Personalization Ability of Large Language Model Agents

This work introduces personalized product search (PPS), a testbed for agentic personalization under raw queries and diverse histories, and constructs Agent Personalized Benchmark (APeB) from action logs, pairing underspecified intents with rich histories and user-viewed candidate items.

Gary Yang, Zi-Zhe Chen, Xinru Chen et al. · 0 citations