Yuanhang Yang

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I am a first-year PhD student at the Institute of Science Tokyo (formerly Tokyo Institute of Technology), working under the supervision of Professor Arase. I completed both my Bachelor’s and Master’s degrees at Harbin Institute of Technology.

My research interests mainly lie on efficienct and reliable LLMs capable of learning from experience.

Feel free to contact me at ysngkil@gmail.com (*^▽^*)

有事也好，有乐子也好，尽管联系我~

QQ: 940716916

微信：ysngki

News

May 15, 2025 My paper, UMoE, is now available on arXiv!
May 29, 2024 One paper is accepted to ACL Findings!
Oct 8, 2023 One short paper is accepted to EMNLP!
Sep 15, 2023 This page is created!

Publications

2025

  1. Arxiv
    UMoE: Unifying Attention and FFN with Shared Experts
    Yuanhang Yang, Chaozheng Wang, and Jing Li
    2025
    arXiv

2024

  1. ACL Findings
    XMoE: Sparse Models with Fine-grained and Adaptive Expert Selection
    Yuanhang Yang, Shiyi Qi, Wenchao Gu, Chaozheng Wang, Cuiyun Gao, and Zenglin Xu
    2024
    arXiv

2023

  1. EMNLP Short
    Once is Enough: A Light-Weight Cross-Attention for Fast Sentence Pair Modeling
    Yuanhang Yang, Shiyi Qi, Chuanyi Liu, Qifan Wang, Cuiyun Gao, and Zenglin Xu
    2023
    arXiv
  2. TOSEM
    TopicAns: Topic-Informed Architecture for Answer Recommendation on Technical Q&A Site
    Yuanhang Yang, Wei He, Cuiyun Gao, Zenglin Xu, Xin Xia, and Chuanyi Liu
    ACM Transactions on Software Engineering and Methodology, 2023
  3. ACL Findings
    FedPETuning: When Federated Learning Meets the Parameter-Efficient Tuning Methods of Pre-trained Language Models
    Zhuo Zhang, Yuanhang Yang, Yong Dai, Qifan Wang, Yue Yu, Lizhen Qu, and Zenglin Xu
    In Findings of the Association for Computational Linguistics: ACL 2023, 2023
    arXiv

2022

  1. FSE
    No more fine-tuning? an experimental evaluation of prompt tuning in code intelligence
    Chaozheng Wang, Yuanhang Yang, Cuiyun Gao, Yun Peng, Hongyu Zhang, and Michael R. Lyu
    Proceedings of the 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering, 2022
    arXiv