Wei-Lin Chen

I am a 3rd-year CS PhD student at the University of Virginia, where I am fortunate to be advised by Prof. Yu Meng and supported by UVA Provost’s Fellowship and UVA Computer Science Scholar Fellowship.

I build AI to think efficiently and evaluate AI verifiably, from reducing reasoning length (Deep-Thinking Tokens), to grounding model evaluation (Self-Preference) and agent safety (VeriHarm) in verifiable environments.

I also spent the past two summers at Google as a Student Researcher, working on efficient test-time reasoning and generalizable agent memory.

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Last updated: October 31, 2026

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Select Research

*equal contribution

New
Think Deep, Not Just Long: Measuring LLM Reasoning Effort via Deep-Thinking Tokens
Wei-Lin Chen, Liqian Peng, Tian Tan, Chao Zhao, Blake JianHang Chen, Ziqian Lin, Alec Go, Yu Meng
ICML 2026
arXiv / thread
New
VeriHarm-Bench: Measuring Harmful Success in LLM Coding Agents Verifiably
Wei-Lin Chen, Zhepei Wei, Xinyu Zhu, Yu-Min Tseng, Tzu-Han Lin, Yu Meng
Preprint
arXiv / thread
Do LLM Evaluators Prefer Themselves for a Reason?
Wei-Lin Chen, Zhepei Wei, Xinyu Zhu, Shi Feng, Yu Meng
Preprint
arXiv / thread
The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning
Xinyu Zhu, Mengzhou Xia, Zhepei Wei, Wei-Lin Chen, Danqi Chen, Yu Meng
NeurIPS 2025
arXiv / thread
Evaluating Large Language Models as Expert Annotators
Yu-Min Tseng, Wei-Lin Chen, Chung-Chi Chen, Hsin-Hsi Chen
COLM 2025
arXiv / thread
InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales
Zhepei Wei, Wei-Lin Chen, Yu Meng
ICLR 2025
arXiv / thread
Two Tales of Persona in LLMs: A Survey of Role-Playing and Personalization
Yu-Min Tseng\(^*\), Yu-Chao Huang\(^*\), Teng-Yun Hsiao\(^*\),Wei-Lin Chen\(^*\), Chao-Wei Huang, Yu Meng, Yun-Nung Chen
EMNLP 2024 Findings
arXiv / repo
Self-ICL: Zero-Shot In-Context Learning with Self-Generated Demonstrations
Wei-Lin Chen\(^*\), Cheng-Kuang Wu\(^*\), Yun-Nung Chen, Hsin-Hsi Chen
EMNLP 2023
arXiv / poster