Kuan-Hao Huang

I am a postdoc at the University of Illinois Urbana-Champaign, collaborating with Heng Ji. I received my Ph.D. in computer science at the University of California Los Angeles, where I worked with Kai-Wei Chang and Nanyun Peng. Prior to that, I obtained my M.S. and B.S. from National Taiwan University, where I was advised by Hsuan-Tien Lin. My research primarily focuses on natural language processing and machine learning. I am particularly passionate about advancing NLP models to read, comprehend, and think like humans. To achieve this goal, I am dedicated to enhancing the ability of NLP models to extract and understand abstract concepts, as well as their capacity to generalize to new domains and novel concepts. The key highlights of my research include the following topics:

  • Abstract concept recognition: guiding NLP models to extract and identify meaningful information from texts (DEGREE, AMPERE, TagPrime).
  • Robust text representation: developing robust text representations that capture semantic meaning and recognize semantically equivalent texts (SynPG, ParaBART, AMRPG, ParaAMR).
  • Knowledge generalization: transferring the acquired knowledge of NLP models to novel domains (GENEVA, PrefixEmb) and unseen languages (RobustXLT, X-Gear, SALT, CLAP).

I am on the faculty job market this year. Feel free to contact me!


  • [2024/01] Our paper about spurious correlations in text classification is accepted by EACL-Findings 2024
  • [2023/11] Please check out our TextEE project about benchmakring event extraction
  • [2023/10] Our paper about easily updated text representations is accepted by EMNLP-Findings 2023
  • [2023/09] Please check out our AACL 2023 paper about zero-shot cross-lingual transfer
  • [2023/07] Our ParaAMR paper receives ACL 2023 Area Chair Award




  • Area Chair/Action Editor
    • Natural Language Processing: ACL Rolling Review (2024), ACL (2024)
  • Program Committee/Reviewer
    • Natural Language Processing: ACL Rolling Review (2021-2023), ACL (2021-2023), EMNLP (2021-2023), NAACL (2022-2024), EACL (2023-2024), COLM (2024)
    • Machine Learning: ICML (2020-2024), NeurIPS (2021-2023), ICLR (2021-2024), TMLR (2024)
    • Artificial Intelligence: AAAI (2022-2024)
  • Handbook Assistant
    • EMNLP 2018