I am a Ph.D. student in Computer Science at UCSD advised by Jingbo Shang. Previously, I was an AI resident at Google Research. I received my B.A. in Computational Linguistics from Peking University.

My research interests are interdisciplinary, including (1) using computational methods to investigate fundamental linguistic questions and (2) applying findings from linguistics to develop techniques for automatic natural language understanding. I am honored to be selected as a DeepMind Scholar.


  • University of California, San Diego
    Sep. 2021 - Present
    Ph.D. in Computer Science

  • The Department of Chinese Language and Literature, Peking University
    Sept. 2015 - Jul. 2019
    B.A. in Computational Linguistics


  • Natural Language Understanding Team, Google Research
    Jun. 2022 - Sep. 2022
    Student Researcher

  • Natural Language Understanding Team, Google Research
    Oct. 2019 - Sep. 2021
    AI Resident

  • Knowledge Computing Group, Microsoft Research Asia
    Apr. 2019 - Jul. 2019
    Research Intern

  • Chinese Language Processing Group, Computer Science Department, Brandeis University
    Jul. 2018 - Sept. 2018
    Research Assistant

  • Key Laboratory of Computational Linguistics, Peking University
    Jul. 2016 - Feb. 2018
    Research Assistant

Selected Publication

  • Retrieval-Augmented Parsing for Complex Graphs by Exploiting Structure and Uncertainty
    Zi Lin, Quan Yuan, Panupong Pasupat, Jeremiah Zhe Liu, Jingbo Shang
    EMNLP findings 2023
    Paper | Code

  • ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation
    Zi Lin*, Zihan Wang*, Yongqi Tong, Yangkun Wang, Yuxin Guo, Yujia Wang, Jingbo Shang
    EMNLP findings 2023
    Arxiv | Blog | Data

  • Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90% ChatGPT Quality
    Wei-Lin Chiang*, Zhuohan Li*, Zi Lin*, Ying Sheng*, Zhanghao Wu*, Hao Zhang*, Lianmin Zheng*, Siyuan Zhuang*, Yonghao Zhuang*, Joseph E. Gonzalez, Ion Stoica, Eric P. Xing
    Blogpost 2023
    Blog | Demo | Code

  • On Compositional Uncertainty Quantification for Seq2seq Graph Parsing
    Zi Lin, Du Phan, Panupong Pasupat, Jeremiah Liu, Jingbo Shang
    ICLR 2023
    Paper | Code

  • A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
    Jeremiah Liu, Shreyas Padhy, Jie Ren, Zi Lin, Yeming Wen, Ghassen Jerfel, Zachary Nado, Jasper Snoek, Dustin Tran, Balaji Lakshminarayanan
    JMLR 2023
    Paper | Arxiv | Code

  • Neural-Symbolic Inference for Robust Autoregressive Graph Parsing via Compositional Uncertainty Quantification
    Zi Lin, Jeremiah Liu, Jingbo Shang
    EMNLP 2022
    Paper | Arxiv | Code

  • Towards Collaborative Neural-Symbolic Graph Semantic Parsing via Uncertainty
    Zi Lin, Jeremiah Liu, Jingbo Shang
    ACL Findings 2022
    Paper | Slides

  • Measuring and Improving Model-Moderator Collaboration using Uncertainty Estimation
    Ian D. Kivlichan*, Zi Lin*, Jeremiah Liu*, Lucy Vasserman
    ACL 2021 workshop on Online Abuse and Harms (WOAH)
    Paper | Slides | Arxiv | Code

  • Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
    Jeremiah Liu, Zi Lin, Shreyas Padhy, Dustin Tran, Tania Bedrax-Weiss, Balaji Lakshminarayanan
    Neurips 2020
    Paper | Poster | Arxiv | Code

  • Comparing Knowledge-Intensive and Data-Intensive Models for English Resource Semantic Parsing
    Junjie Cao*, Zi Lin*, Weiwei Sun, Xiaojun Wan
    Computational Linguistics 47 (1), 43-68 (also presented in EACL 2021)
    Paper | Slides | Video | Arxiv
  • Parsing Meaning Representations: is Easier Always Better?
    Zi Lin, Nianwen Xue
    ACL 2019 Workshop on Designing Meaning Representations (DMR)
    Paper | Slides
  • Semantic Role Labeling for Learner Chinese: the Importance of Syntactic Parsing and L2-L1 Parallel Data
    Zi Lin, Yuguang Duan, Yuanyuan Zhao, Weiwei Sun, Xiaojun Wan
    EMNLP 2018
    Paper | Slides | Video | Arxiv | Data


  • I learned western painting for nearly ten years and I still enjoy painting as an amateur, including sketching, acrylic painting and digital painting.