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Chenglei Si (チェンレイ・シ)

[email] [scholar] [twitter] [github]
2nd Year PhD at Stanford NLP

About

 At Stanford, I'm advised by the wonderful Tatsu Hashimoto and Diyi Yang. Before coming to Stanford, I did my undergrad at the University of Maryland where I was advised by Jordan Boyd-Graber. I also had the fortune to work with many amazing research mentors and collaborators, including Michael Bernstein, Hal Daumé III, He He, Danqi Chen, Sherry Wu, Zhiyuan Liu, Min-Yen Kan, and many others.

I'm interested in how LLMs can transform scientific research, and new forms of human-AI co-intelligence. Towards this end, I split my time between working with LLMs and running human studies. When not writing papers, I also write research related threads for fun.

Research style: I've come to the realization that I'm most productive when focusing on only 1-2 projects every year. And I prefer projects that are more ambitious and risky in nature (which also tend to be longer-term). This means that I have to turn down all the collaboration requests that don't fall into this category -- I'm sorry!

Selected Papers
  • The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas
    Chenglei Si, Tatsunori Hashimoto, Diyi Yang
    preprint [paper] [data] [tweet]

  • Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers
    Chenglei Si, Diyi Yang, Tatsunori Hashimoto
    ICLR 2025 [paper] [code] [tweet] [Nature News] [Newsweek] [Synced]

  • Predicting Empirical AI Research Outcomes with Language Models
    Jiaxin Wen, Chenglei Si, Yueh-han Chen, He He, Shi Feng
    preprint [paper] [tweet]

Talks
  • Fall 2024: The Dream of Automating Research (Part 1)
    Stanford, USC, MIT, Northeastern, MILA, Intel, Samaya AI
    [slides] [podcast]


Conference Travels
  • April 2025, ICLR @ Singapore
  • Dec 2024, NeurIPS @ Vancouver
  • 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