Yuan Wu

Associate Professor, School of Artificial Intelligence, Jilin University

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School of Artificial Intelligence

Jilin University

I am a pre-tenured associate professor at the School of Artificial Intelligence, Jilin University. My research interests include natural language processing, large language models, LLM evaluation, and LLM post-training.

I received my Bachelor degree from Beijing University of Chemical Technology, my Master degree from Lanzhou University, advised by Prof. Lian Li, and my Ph.D. from Carleton University, advised by Prof. Ahmed El-Roby and Prof. Diana Inkpen.

My group studies reliable, efficient, and trustworthy methods for building and evaluating large language models. I welcome inquiries from undergraduate and graduate students interested in natural language processing, LLM evaluation, post-training, domain adaptation, and trustworthy AI.

Research Interests

  • Large language model evaluation and benchmarking
  • LLM post-training and parameter-efficient fine-tuning
  • Trustworthy and reliable language models
  • Domain adaptation and generalization for NLP
  • Instruction following and model self-evaluation

News

Aug, 2026
6 papers have been accepted to EMNLP 2026.
Apr, 2026
4 papers have been accepted to ACL 2026.
Jan, 2026
1 paper has been accepted to ICLR 2026.
Aug, 2025
6 papers have been accepted to EMNLP 2025.
Apr, 2025
1 paper has been accepted to ACL 2025.

selected publications

  1. BA-LoRA: Bias-Alleviating Low-Rank Adaptation to Mitigate Catastrophic Inheritance in Large Language Models
    Yupeng Chang, Yi Chang, and Yuan Wu+
    In ICLR, 2026
  2. AGGC: Adaptive Group Gradient Clipping for Stabilizing Large Language Model Training
    Zhiyuan Li, Yuan Wu+, and Yi Chang
    In Findings of ACL, 2026
  3. Rethinking Data Selection at Scale: Random Selection is Almost All You Need
    Tingyu Xia, Bowen Yu, Kai Dang, An Yang, Yuan Wu+, Yuan Tian, Yi Chang, and Junyang Lin
    In Findings of EMNLP, 2025
  4. StructFlowBench: A Structured Flow Benchmark for Multi-Turn Instruction Following
    Jinnan Li, Jinzhe Li, Yue Wang, Yi Chang, and Yuan Wu+
    In Findings of ACL, 2025
  5. A Survey on Evaluation of Large Language Models
    Yupeng Chang, Xu Wang, Jindong Wang, Yuan Wu+, Linyi Yang, Kaijie Zhu, Hao Chen, Xiaoyuan Yi, Cunxiang Wang, Yidong Wang, Wei Ye, Yue Zhang, Yi Chang, Philip S. Yu, Qiang Yang, and Xing Xie
    ACM Transactions on Intelligent Systems and Technology, 2024
  6. Language Models can Evaluate Themselves via Probability Discrepancy
    Tingyu Xia, Bowen Yu, Yuan Wu+, Yi Chang, and Chang Zhou
    In Findings of ACL, 2024