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2020 – today
- 2025
[i13]Long Phan, Alice Gatti, Ziwen Han, Nathaniel Li, Josephina Hu, Hugh Zhang, Sean Shi, Michael Choi, Anish Agrawal, Arnav Chopra, Adam Khoja, Ryan Kim, Jason Hausenloy, Oliver Zhang, Mantas Mazeika, Daron Anderson, Tung Nguyen, Mobeen Mahmood, Fiona Feng, Steven Y. Feng, Haoran Zhao, Michael Yu, Varun Gangal, Chelsea Zou, Zihan Wang, Jessica P. Wang, Pawan Kumar, Oleksandr Pokutnyi, Robert Gerbicz, Serguei Popov, John-Clark Levin, Mstyslav Kazakov, Johannes Schmitt, Geoff Galgon, Alvaro Sanchez, Yongki Lee, Will Yeadon, Scott Sauers, Marc Roth, Chidozie Agu, Søren Riis, Fabian Giska, Saiteja Utpala, Zachary Giboney, Gashaw M. Goshu, Joan of Arc Xavier, Sarah-Jane Crowson, Mohinder Maheshbhai Naiya, Noah Burns, Lennart Finke
, Zerui Cheng, Hyunwoo Park, Francesco Fournier-Facio, John Wydallis, Mark Nandor, Ankit Singh, Tim Gehrunger, Jiaqi Cai, Ben McCarty, Darling Duclosel, Jungbae Nam, Jennifer Zampese, Ryan G. Hoerr, Aras Bacho, Gautier Abou Loume, Abdallah Galal, Hangrui Cao, Alexis C. Garretson, Damien Sileo, Qiuyu Ren, Doru Cojoc, Pavel Arkhipov, Usman Qazi, Lianghui Li, Sumeet Motwani, Christian Schröder de Witt, Edwin Taylor, Johannes Veith, Eric Singer, Taylor D. Hartman, Paolo Rissone, Jaehyeok Jin, Jack Wei Lun Shi, Chris G. Willcocks, Joshua Robinson, Aleksandar Mikov, Ameya Prabhu, Longke Tang, Xavier Alapont, Justine Leon Uro, Kevin Zhou, Emily de Oliveira Santos, Andrey Pupasov Maksimov, Edward Vendrow, Kengo Zenitani, Julien Guillod, Yuqi Li, Joshua Vendrow, Vladyslav Kuchkin, Ng Ze-An:
Humanity's Last Exam. CoRR abs/2501.14249 (2025)- 2024
- [c6]Kenneth Li, Samy Jelassi, Hugh Zhang, Sham M. Kakade, Martin Wattenberg, David Brandfonbrener:
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models. ICML 2024 - [c5]Vaskar Nath, Dylan Slack, Jeff Da, Yuntao Ma, Hugh Zhang, Spencer Whitehead, Sean Hendryx:
Learning Goal-Conditioned Representations for Language Reward Models. NeurIPS 2024 - [c4]Hugh Zhang, Jeff Da, Dean Lee, Vaughn Robinson, Catherine Wu, William Song, Tiffany Zhao, Pranav Raja, Charlotte Zhuang, Dylan Slack, Qin Lyu, Sean Hendryx, Russell Kaplan, Michele Lunati, Summer Yue:
A Careful Examination of Large Language Model Performance on Grade School Arithmetic. NeurIPS 2024 - [i12]Luca D'Amico-Wong, Hugh Zhang, Marc Lanctot, David C. Parkes:
Easy as ABCs: Unifying Boltzmann Q-Learning and Counterfactual Regret Minimization. CoRR abs/2402.11835 (2024) - [i11]Kenneth Li, Samy Jelassi, Hugh Zhang, Sham M. Kakade, Martin Wattenberg, David Brandfonbrener:
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models. CoRR abs/2402.14688 (2024) - [i10]Hugh Zhang, Jeff Da, Dean Lee, Vaughn Robinson, Catherine Wu, Will Song, Tiffany Zhao, Pranav Raja, Dylan Slack, Qin Lyu, Sean Hendryx, Russell Kaplan, Michele Lunati, Summer Yue:
A Careful Examination of Large Language Model Performance on Grade School Arithmetic. CoRR abs/2405.00332 (2024) - [i9]Huaixiu Steven Zheng, Swaroop Mishra, Hugh Zhang, Xinyun Chen, Minmin Chen, Azade Nova, Le Hou, Heng-Tze Cheng, Quoc V. Le, Ed H. Chi, Denny Zhou:
NATURAL PLAN: Benchmarking LLMs on Natural Language Planning. CoRR abs/2406.04520 (2024) - [i8]Vaskar Nath, Dylan Slack, Jeff Da, Yuntao Ma, Hugh Zhang, Spencer Whitehead, Sean Hendryx:
Learning Goal-Conditioned Representations for Language Reward Models. CoRR abs/2407.13887 (2024) - [i7]Nathaniel Li, Ziwen Han, Ian Steneker, Willow Primack, Riley Goodside, Hugh Zhang, Zifan Wang, Cristina Menghini, Summer Yue:
LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet. CoRR abs/2408.15221 (2024) - [i6]Evan Wang, Federico Cassano, Catherine Wu, Yunfeng Bai, Will Song, Vaskar Nath, Ziwen Han, Sean Hendryx, Summer Yue, Hugh Zhang:
Planning In Natural Language Improves LLM Search For Code Generation. CoRR abs/2409.03733 (2024) - 2023
- [c3]Hugh Zhang:
No-regret Learning Dynamics for Sequential Correlated Equilibria. AAMAS 2023: 2700-2702 - [i5]Hugh Zhang, David C. Parkes:
Chain-of-Thought Reasoning is a Policy Improvement Operator. CoRR abs/2309.08589 (2023) - 2022
- [c2]Hugh Zhang, Adam Lerer, Noam Brown:
Equilibrium Finding in Normal-Form Games via Greedy Regret Minimization. AAAI 2022: 9484-9492 - [i4]Hugh Zhang, Adam Lerer, Noam Brown:
Equilibrium Finding in Normal-Form Games Via Greedy Regret Minimization. CoRR abs/2204.04826 (2022) - [i3]Hugh Zhang:
A Simple Adaptive Procedure Converging to Forgiving Correlated Equilibria. CoRR abs/2207.06548 (2022) - 2020
- [i2]Hugh Zhang, Daniel Duckworth, Daphne Ippolito, Arvind Neelakantan:
Trading Off Diversity and Quality in Natural Language Generation. CoRR abs/2004.10450 (2020)
2010 – 2019
- 2019
- [c1]Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang:
Unifying Human and Statistical Evaluation for Natural Language Generation. NAACL-HLT (1) 2019: 1689-1701 - [i1]Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang:
Unifying Human and Statistical Evaluation for Natural Language Generation. CoRR abs/1904.02792 (2019)
Coauthor Index
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