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ORCIDRyan Liu 0001
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- affiliation: Princeton University, Department of Computer Science, Princeton, NJ, USA
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- Ryan Liu — disambiguation page
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2020 – today
- 2026
[c12]Kaiqu Liang, Haimin Hu, Ryan Liu, Thomas L. Griffiths, Jaime Fernández Fisac:
RLHS: Mitigating Misalignment in RLHF with Hindsight Simulation. ACL (Findings) 2026: 11457-11483- [i21]Ryan Liu, Dilip Arumugam, Cedegao E. Zhang, Sean Escola, Xaq Pitkow, Thomas L. Griffiths:
Cognitive Models and AI Algorithms Provide Templates for Designing Language Agents. CoRR abs/2602.22523 (2026) - [i20]Addison J. Wu, Ryan Liu, Shuyue Stella Li, Yulia Tsvetkov, Thomas L. Griffiths:
Ads in AI Chatbots? An Analysis of How Large Language Models Navigate Conflicts of Interest. CoRR abs/2604.08525 (2026) - 2025
- [c11]Tongshuang Wu
, Haiyi Zhu, Maya Albayrak, Alexis Axon, Amanda Bertsch, Wenxing Deng, Ziqi Ding, Boyuan 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:
LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs. CHI Extended Abstracts 2025: 684:1-684:10 - [c10]Ryan Liu, Howard Yen, Raja Marjieh, Tom Griffiths, Ranjay Krishna:
Improving Interpersonal Communication by Simulating Audiences with Large Language Models. CogSci 2025 - [c9]Ryan Liu, Jiayi Geng, Joshua C. Peterson, Ilia Sucholutsky, Thomas L. Griffiths:
Large Language Models Assume People are More Rational than We Really are. ICLR 2025 - [c8]Ryan Liu, Jiayi Geng, Addison J. Wu, Ilia Sucholutsky, Tania Lombrozo, Thomas L. Griffiths:
Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse. ICML 2025 - [c7]Jacy Reese Anthis, Ryan Liu, Sean M. Richardson, Austin C. Kozlowski, Bernard Koch, Erik Brynjolfsson, James A. Evans, Michael S. Bernstein:
Position: LLM Social Simulations Are a Promising Research Method. ICML (Position Papers) 2025 - [c6]Addison J. Wu, Ryan Liu, Kerem Oktar, Theodore R. Sumers, Tom Griffiths:
Are Large Language Models Sensitive to the Motives Behind Communication? NeurIPS 2025 - [i19]Kaiqu Liang, Haimin Hu, Ryan Liu, Thomas L. Griffiths, Jaime Fernández Fisac:
RLHS: Mitigating Misalignment in RLHF with Hindsight Simulation. CoRR abs/2501.08617 (2025) - [i18]Lance Ying, Katherine M. Collins, Lionel Wong, Ilia Sucholutsky, Ryan Liu, Adrian Weller, Tianmin Shu, Thomas L. Griffiths, Joshua B. Tenenbaum:
On Benchmarking Human-Like Intelligence in Machines. CoRR abs/2502.20502 (2025) - [i17]Alexander Ku, Declan Campbell, Xuechunzi Bai, Jiayi Geng, Ryan Liu, Raja Marjieh, R. Thomas McCoy, Andrew Nam, Ilia Sucholutsky, Veniamin Veselovsky, Liyi Zhang, Jian-Qiao Zhu, Thomas L. Griffiths:
Using the Tools of Cognitive Science to Understand Large Language Models at Different Levels of Analysis. CoRR abs/2503.13401 (2025) - [i16]Jacy Reese Anthis, Ryan Liu, Sean M. Richardson, Austin C. Kozlowski, Bernard Koch, James A. Evans, Erik Brynjolfsson, Michael S. Bernstein:
LLM Social Simulations Are a Promising Research Method. CoRR abs/2504.02234 (2025) - [i15]Katherine M. Collins, Cedegao E. Zhang, Graham Todd, Lance Ying, Mauricio Barba da Costa, Ryan Liu, Prafull Sharma, Adrian Weller, Ionatan Kuperwajs, Lionel Wong, Joshua B. Tenenbaum, Thomas L. Griffiths:
Evaluating Language Models' Evaluations of Games. CoRR abs/2510.10930 (2025) - [i14]Addison J. Wu, Ryan Liu, Kerem Oktar, Theodore R. Sumers, Thomas L. Griffiths:
Are Large Language Models Sensitive to the Motives Behind Communication? CoRR abs/2510.19687 (2025) - [i13]Jiayi Geng, Howard Chen, Ryan Liu, Manoel Horta Ribeiro, Robb Willer, Graham Neubig, Thomas L. Griffiths:
Accumulating Context Changes the Beliefs of Language Models. CoRR abs/2511.01805 (2025) - [i12]Addison J. Wu, Ryan Liu, Xuechunzi Bai, Thomas L. Griffiths:
Large Language Models Develop Novel Social Biases Through Adaptive Exploration. CoRR abs/2511.06148 (2025) - 2024
- [c5]Ryan Liu, Theodore R. Sumers, Ishita Dasgupta, Thomas L. Griffiths:
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness? ICML 2024: 31844-31865 - [i11]Ryan Liu, Theodore R. Sumers, Ishita Dasgupta, Thomas L. Griffiths:
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness? CoRR abs/2402.07282 (2024) - [i10]Ryan Liu, Jiayi Geng, Joshua C. Peterson, Ilia Sucholutsky, Thomas L. Griffiths:
Large Language Models Assume People are More Rational than We Really are. CoRR abs/2406.17055 (2024) - [i9]Ryan Liu, Jiayi Geng, Addison J. Wu, Ilia Sucholutsky, Tania Lombrozo, Thomas L. Griffiths:
Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse. CoRR abs/2410.21333 (2024) - 2023
- [c4]Yihan Cao, Shuyi Chen, Ryan Liu, Zhiruo Wang, Daniel Fried:
API-Assisted Code Generation for Question Answering on Varied Table Structures. EMNLP 2023: 14536-14548 - [i8]Ryan Liu, Nihar B. Shah:
ReviewerGPT? An Exploratory Study on Using Large Language Models for Paper Reviewing. CoRR abs/2306.00622 (2023) - [i7]Ryan Liu, Steven Jecmen, Vincent Conitzer, Fei Fang, Nihar B. Shah:
Testing for Reviewer Anchoring in Peer Review: A Randomized Controlled Trial. CoRR abs/2307.05443 (2023) - [i6]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:
LLMs as Workers in Human-Computational Algorithms? Replicating Crowdsourcing Pipelines with LLMs. CoRR abs/2307.10168 (2023) - [i5]Yihan Cao, Shuyi Chen, Ryan Liu, Zhiruo Wang, Daniel Fried:
API-Assisted Code Generation for Question Answering on Varied Table Structures. CoRR abs/2310.14687 (2023) - [i4]Ryan Liu, Howard Yen, Raja Marjieh, Thomas L. Griffiths, Ranjay Krishna:
Improving Interpersonal Communication by Simulating Audiences with Language Models. CoRR abs/2311.00687 (2023) - 2022
- [c3]Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah:
Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design. AAMAS 2022: 1642-1644 - [c2]Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah:
Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design. HCOMP 2022: 102-113 - [i3]Ivan Stelmakh, Charvi Rastogi, Ryan Liu, Shuchi Chawla, Federico Echenique, Nihar B. Shah:
Cite-seeing and Reviewing: A Study on Citation Bias in Peer Review. CoRR abs/2203.17239 (2022) - 2021
- [i2]Steven Jecmen, Hanrui Zhang, Ryan Liu, Fei Fang, Vincent Conitzer, Nihar B. Shah:
Near-Optimal Reviewer Splitting in Two-Phase Paper Reviewing and Conference Experiment Design. CoRR abs/2108.06371 (2021) - 2020
- [c1]Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang:
Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments. NeurIPS 2020 - [i1]Steven Jecmen, Hanrui Zhang, Ryan Liu, Nihar B. Shah, Vincent Conitzer, Fei Fang:
Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments. CoRR abs/2006.16437 (2020)
Coauthor Index
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