Ryan Liu

Email: ryanliu@princeton.edu   LinkedIn: ryanchenliu  GitHub: theryanl  Google Scholar: link   CV: pdf

Hi! I am a first year PhD student at Princeton Computer Science advised by Tom Griffiths and Andrés Monroy-Hernández. The central focus of my research is how large language models can transform how our society communicates and learns information. Previously, I was a Masters student at Carnegie Mellon working with Nihar Shah on solving central problems in conference peer review.

I am happy to chat about my current research and future opportunities! Please contact me via email at ryanliu@princeton.edu.

Papers

• How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
  Ryan Liu*, Theodore R. Sumers*, Ishita Dasgupta, and Thomas L. Griffiths
  Under Review [arXiv]


• Improving Interpersonal Communication by Simulating Audiences with Language Models
  Ryan Liu, Howard Yen, Raja Marjieh, Thomas L. Griffiths, and Ranjay Krishna
  Under Review [arXiv]


• API-Assisted Code Generation for Question Answering on Varied Table Structures
  Yihan Cao*, Shuyi Chen*, Ryan Liu*, Zhiruo Wang, and Daniel Fried
  EMNLP 2023 [arXiv]


• ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing
  Ryan Liu and Nihar B. Shah
  Oral, AAAI SDU Workshop 2024 [arXiv]


• LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs
  Tongshuang Wu, Haiyi Zhu, Maya Albayrak, Alexis Axon, Amanda Bertsch, Wenxing Deng, Ziqi Ding, Bill Guo, Sireesh Gururaja, Tzu-Sheng Kuo, Jenny T Liang, Ryan Liu, Ihita Mandal, Jeremiah Milbauer, Xiaolin Ni, Namrata Padmanabhan, Subhashini Ramkumar, Alexis Sudjianto, Jordan Taylor, Ying-Jui Tseng, Patricia Vaidos, Zhijin Wu, Wei Wu, Chenyang Yang
  [arXiv]


• Testing for Reviewer Anchoring in Peer Review: A Randomized Controlled Trial
  Ryan Liu, Steven Jecmen, Fei Fang, Vincent Conitzer, and Nihar B. Shah
  Under Review [arXiv]


• Cite-seeing and Reviewing: A Study on Citation Bias in Peer Review
  Ivan Stelmakh, Charvi Rastogi, Ryan Liu, Shuchi Chawla, Federico Echenique, and Nihar B. Shah
  PLoS ONE [arXiv]


• Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing & Conference Experiment Design
  Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, and Nihar B. Shah
  AAAI HCOMP 2022, Best Paper Honorable Mention [arXiv]


• Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments
  Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, and Fei Fang
  NeurIPS 2020 [arXiv]

Presentations

• Moderator @ London Machine Learning Meetup
  Joon Sung Park | Generative Agents: Interactive Simulacra of Human Behavior [recording]
• Podcast @ Data Skeptic
  Automated Peer Review [link]
• Visit @ Allen Institute for AI, Semantic Scholar Team
  
• Talk @ Carnegie Mellon University Meeting of the Minds 2022
  Identifying Human Biases in Peer Review via Real-Subject Experiments
• Poster @ Carnegie Mellon University Meeting of the Minds 2021
  Improving Algorithmic Tools for Conference Peer Review Research
• Poster @ Carnegie Mellon University Fall Undergraduate Research Showcase 2020
  Creating Robustness within Conference Peer Review
• Poster @ Carnegie Mellon University Meeting of the Minds 2020
  Assignment Algorithms to Prevent Quid-Pro-Quo in Conference Peer Review

Experience

• AI/ML SWE Internship @ Meta
  
• Teaching Assistant @ CMU 15-112 Fundamentals of Programming
  
• Research Assistant @ CMU School of Computer Science
  

Academic Honors

• Student Organizer, Decentralized Social Media Workshop @Princeton
  
• NSF Research Experience for Undergraduates Grant (CMU)
  
• Bachelor of Science, CMU School of Computer Science, College & University Honors
  
• Fifth-Year Master's, CMU School of Computer Science, Thesis: Testing for Reviewer Anchoring in the Conference Rebuttal Process [link]