Pei Zhou

Pei Zhou

I am a final-year PhD candidate in computer science at University of Southern California, where I work in the USC-NLP Group. My advisors are Xiang Ren and Jay Pujara. I'm interested in improving and evaluating large language models (LLM) reasoning, communicating agents, and human-AI collaboration for new discoveries.

Previously, I received undergraduate degree in Mathematics of Computation from University of California, Los Angeles (UCLA), where I worked with Kai-Wei Chang and Yizhou Sun. I've also interned at Google Bard (working with Shyam Upadhyay and Manaal Faruqui, Allen Institute for Artificial Intelligence (AI2) (working with Prithviraj Ammanabrolu, Chris Callison-Burch, and Yejin Choi), and Amazon Alexa AI (working with Yang Liu and Dilek Hakkani-Tur).

Currently, I am a Research Collaborator at Google DeepMind (working with Swaroop Mishra, Huaixiu Steven Zheng, Denny Zhou, and Quoc V. Le).
I'm on the job market this year! If you are hiring and interested, drop me an email, I'm more than happy to chat :-)

[Full CV] [Twitter] [LinkedIn] [Github] [Google Scholar] [Semantic Scholar]

Recent News

  • [December 2023] Attending NeurIPS in New Orleans, come say hi!
  • [September 2023] Started my collaboration with Google DeepMind working on LLM meta-task reasoning!
  • [July 2023] Attending ACL at Toronto, come say hi! I'll be presenting our paper on a Dungeon Master-like dialogue agent in D&D with theory-of-mind and RL!
  • [May 2023] Started my internship at Google Bard working on theory-of-mind capabilities in LLMs!
  • [April 2023] Our Theory-of-Mind workshop is accepted in ICML 2023! Hope to see you in Honolulu in July!


Aug 2019 - Present (Expected May 2024)
Ph.D. in Computer Science, University of Southern California

Sep 2015 - June 2019
B.S. in Mathematics of Computation with Minor in Statistics, University of California, Los Angeles (UCLA)

Selected Publications

(Full list see Google Scholar)

  • How FaR Are Large Language Models From Agents with Theory-of-Mind?
    Pei Zhou, Aman Madaan, Srividya Pranavi Potharaju, Aditya Gupta, Kevin R. McKee, Ari Holtzman, Jay Pujara, Xiang Ren, Swaroop Mishra Aida Nematzadeh, Shyam Upadhyay, and Manaal Faruqui.
    Preprint, 2023.

  • SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization
    Hyunwoo Kim, Jack Hessel, Liwei Jiang, Peter West, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Le Bras, Malihe Alikhani Gunhee Kim, Maarten Sap, and Yejin Choi.
    In EMNLP, 2023. Outstanding Paper Award

  • I Cast Detect Thoughts: Learning to Converse and Guide with Intents and Theory-of-Mind in Dungeons and Dragons
    Pei Zhou, Andrew Zhu, Jennifer Hu, Jay Pujara, Xiang Ren, Chris Callison-Burch, Yejin Choi, and Prithviraj Ammanabrolu.
    In ACL, 2023.
    [abstract] [media coverage]

  • Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response Quality
    Pei Zhou, Hyundong Cho, Pegah Jandaghi, Dong-Ho Lee, Bill Yuchen Lin, Jay Pujara, and Xiang Ren.
    In EMNLP, 2022.
    [abstract] [project page] [dataset] [media coverage]

  • Think Before You Speak: Explicitly Generating Implicit Commonsense Knowledge for Response Generation
    Pei Zhou, Karthik Gopalakrishnan, Behnam Hedayatnia, Seokhwan Kim, Jay Pujara, Xiang Ren, Yang Liu, and Dilek Hakkani-Tur.
    In ACL, 2022.
    [abstract] [media coverage]

  • Probing Commonsense Explanation in Dialogue Response Generation
    Pei Zhou, Pegah Jandaghi, Hyundong Cho, Bill Yuchen Lin, Jay Pujara, and Xiang Ren.
    In EMNLP-Findings, 2021.

  • Lawyers are Dishonest? Quantifying Representational Harms in Commonsense Knowledge Resources
    Ninareh Mehrabi*, Pei Zhou* (equal contribution), Fred Morstatter, Jay Pujara, Xiang Ren, and Aram Galstyan.
    In EMNLP, 2021.

  • RICA: Evaluating Robust Inference Capabilities Based on Commonsense Axioms
    Pei Zhou, Rahul Khanna, Seyeon Lee, Bill Yuchen Lin, Daniel Ho, Jay Pujara, and Xiang Ren,
    In EMNLP, 2021.
    [abstract] [project page] [data]

  • Commonsense-Focused Dialogues for Response Generation: An Empirical Study
    Pei Zhou, Karthik Gopalakrishnan, Behnam Hedayatnia, Seokhwan Kim, Jay Pujara, Xiang Ren, Yang Liu, and Dilek Hakkani-Tur.
    In SIGDIAL, 2021.
    [abstract] [data] [Amazon blog]

  • CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning
    Bill Yuchen Lin, Wangchunshu Zhou, Ming Shen, Pei Zhou, Chandra Bhagavatula, Yejin Choi, and Xiang Ren.
    In EMNLP-Findings, 2020.
    [abstract] [project page] [data] [media coverage]

  • Examining Gender Bias in Languages with Grammatical Gender
    Pei Zhou, Weijia Shi, Jieyu Zhao, Kuan-Hao Huang, Muhao Chen, Ryan Cotterell, and Kai-Wei Chang.
    In EMNLP-IJCNLP, 2019.
    [abstract] [code]



  • I play the piano and am a keyboardist in UCLA Accoustic Guitar Band called Parked in 4 East
  • I was born in Chengdu, a great city for vacation and spicy food lovers :)
  • Currently super into camping/glamping!
  • I'm into all kinds of RPGs from tabletop to ffxiv
  • Thanks to Nelson Liu for sharing source code of the website!