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my face
(photo credit: Jordan)

Chenglei Si

[email] [scholar] [twitter] [github]
1st Year PhD at Stanford NLP & HCI

About

At Stanford, I'm working with Tatsu Hashimoto, Michael Bernstein, and Diyi Yang. Before coming to Stanford, I did my undergrad at the University of Maryland where I was advised by Jordan Boyd-Graber.

On the AI side, I'm building agents that can automate scientific research: brainstorming novel ideas, planning and executing experiments, and summarizing results. On the HCI side, I'm interested in designing empirical studies to rigorously understand the impact of AI on humans, both at the individual level and at the societal level.

When not writing papers, I also write research related Twitter threads for fun.

Selected Papers

  • Design2Code: How Far Are We From Automating Front-End Engineering?
    Chenglei Si*, Yanzhe Zhang*, Zhengyuan Yang, Ruibo Liu, Diyi Yang
    preprint [paper] [code] [project page] [tweet]

  • Large Language Models Help Humans Verify Truthfulness -- Except When They Are Convincingly Wrong
    Chenglei Si, Navita Goyal, Sherry Tongshuang Wu, Chen Zhao, Shi Feng, Hal Daumé III, Jordan Boyd-Graber
    NAACL 2024 [paper] [tweet]

  • Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations
    Chenglei Si*, Dan Friedman*, Nitish Joshi, Shi Feng, Danqi Chen, He He
    ACL 2023 [paper] [code] [tweet] [OpenReview]

  • Prompting GPT-3 To Be Reliable
    Chenglei Si, Zhe Gan, Zhengyuan Yang, Shuohang Wang, Jianfeng Wang, Jordan Boyd-Graber, Lijuan Wang
    ICLR 2023 [paper] [code] [tweet] [video]

Conference Travels

  • June 2024, NAACL @ Mexico City
  • Oct 2023, UIST @ San Francisco
  • July 2023, ACL @ Toronto
  • May 2023, ICLR @ Kigali
  • Dec 2022, EMNLP @ Abu Dhabi
  • July 2022, NAACL @ Seattle