Yuhuai Wu

According to our database, Yuhuai Wu authored at least 56 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Solving olympiad geometry without human demonstrations.

Trieu H. Trinh, Yuhuai Wu, Quoc V. Le, He He, Thang Luong

Nat., January, 2024

Don't Trust: Verify - Grounding LLM Quantitative Reasoning with Autoformalization.

Jin Peng Zhou, Charles Staats, Wenda Li, Christian Szegedy, Kilian Q. Weinberger, Yuhuai Wu

CoRR, 2024

REFACTOR: Learning to Extract Theorems from Proofs.

Jin Peng Zhou, Yuhuai Wu, Qiyang Li, Roger B. Grosse

CoRR, 2024

2023

Length Generalization in Arithmetic Transformers.

Samy Jelassi, Stéphane d'Ascoli, Carles Domingo-Enrich, Yuhuai Wu, Yuanzhi Li, François Charton

CoRR, 2023

Evaluating Language Models for Mathematics through Interactions.

Katherine M. Collins, Albert Q. Jiang, Simon Frieder, Lionel Wong, Miri Zilka, Umang Bhatt, Thomas Lukasiewicz, Yuhuai Wu, Joshua B. Tenenbaum, William Hart, Timothy Gowers, Wenda Li, Adrian Weller, Mateja Jamnik

CoRR, 2023

Lexinvariant Language Models.

Qian Huang, Eric Zelikman, Sarah Li Chen, Yuhuai Wu, Gregory Valiant, Percy Liang

CoRR, 2023

Magnushammer: A Transformer-based Approach to Premise Selection.

Maciej Mikula, Szymon Antoniak, Szymon Tworkowski, Albert Qiaochu Jiang, Jin Peng Zhou, Christian Szegedy, Lukasz Kucinski, Piotr Milos, Yuhuai Wu

CoRR, 2023

Focused Transformer: Contrastive Training for Context Scaling.

Szymon Tworkowski, Konrad Staniszewski, Mikolaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Milos

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Lexinvariant Language Models.

Qian Huang, Eric Zelikman, Sarah Chen, Yuhuai Wu, Gregory Valiant, Percy Liang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search.

Michal Zawalski, Michal Tyrolski, Konrad Czechowski, Tomasz Odrzygózdz, Damian Stachura, Piotr Piekos, Yuhuai Wu, Lukasz Kucinski, Piotr Milos

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs.

Albert Qiaochu Jiang, Sean Welleck, Jin Peng Zhou, Timothée Lacroix, Jiacheng Liu, Wenda Li, Mateja Jamnik, Guillaume Lample, Yuhuai Wu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Holistic Evaluation of Language Models.

Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel J. Orr, Lucia Zheng, Mert Yüksekgönül, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri S. Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, Yuta Koreeda

CoRR, 2022

Language Model Cascades.

David Dohan, Winnie Xu, Aitor Lewkowycz, Jacob Austin, David Bieber, Raphael Gontijo Lopes, Yuhuai Wu, Henryk Michalewski, Rif A. Saurous, Jascha Sohl-Dickstein, Kevin Murphy, Charles Sutton

CoRR, 2022

STaR: Bootstrapping Reasoning With Reasoning.

Eric Zelikman, Yuhuai Wu, Noah D. Goodman

CoRR, 2022

STaR: Bootstrapping Reasoning With Reasoning.

Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah D. Goodman

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Insights into Pre-training via Simpler Synthetic Tasks.

Yuhuai Wu, Felix Li, Percy Liang

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Autoformalization with Large Language Models.

Yuhuai Wu, Albert Qiaochu Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Solving Quantitative Reasoning Problems with Language Models.

Aitor Lewkowycz, Anders Andreassen, David Dohan, Ethan Dyer, Henryk Michalewski, Vinay V. Ramasesh, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur, Guy Gur-Ari, Vedant Misra

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers.

Albert Qiaochu Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygózdz, Piotr Milos, Yuhuai Wu, Mateja Jamnik

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Block-Recurrent Transformers.

DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, Behnam Neyshabur

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Exploring Length Generalization in Large Language Models.

Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra, Vinay V. Ramasesh, Ambrose Slone, Guy Gur-Ari, Ethan Dyer, Behnam Neyshabur

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Path Independent Equilibrium Models Can Better Exploit Test-Time Computation.

Cem Anil, Ashwini Pokle, Kaiqu Liang, Johannes Treutlein, Yuhuai Wu, Shaojie Bai, J. Zico Kolter, Roger B. Grosse

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Hierarchical Transformers Are More Efficient Language Models.

Piotr Nawrot, Szymon Tworkowski, Michal Tyrolski, Lukasz Kaiser, Yuhuai Wu, Christian Szegedy, Henryk Michalewski

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

Memorizing Transformers.

Yuhuai Wu, Markus Norman Rabe, DeLesley Hutchins, Christian Szegedy

Proceedings of the Tenth International Conference on Learning Representations, 2022

Invariant Causal Representation Learning for Out-of-Distribution Generalization.

Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf

Proceedings of the Tenth International Conference on Learning Representations, 2022

Proof Artifact Co-Training for Theorem Proving with Language Models.

Jesse Michael Han, Jason Rute, Yuhuai Wu, Edward W. Ayers, Stanislas Polu

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

Discrete Equidecomposability and Ehrhart Theory of Polygons.

Paxton Turner, Yuhuai Wu

Discret. Comput. Geom., 2021

Learning to Give Checkable Answers with Prover-Verifier Games.

Cem Anil, Guodong Zhang, Yuhuai Wu, Roger B. Grosse

CoRR, 2021

Nonlinear Invariant Risk Minimization: A Causal Approach.

Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf

CoRR, 2021

Subgoal Search For Complex Reasoning Tasks.

Konrad Czechowski, Tomasz Odrzygózdz, Marek Zbysinski, Michal Zawalski, Krzysztof Olejnik, Yuhuai Wu, Lukasz Kucinski, Piotr Milos

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning.

Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy

Proceedings of the 38th International Conference on Machine Learning, 2021

Efficient Statistical Tests: A Neural Tangent Kernel Approach.

Sheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba

Proceedings of the 38th International Conference on Machine Learning, 2021

INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving.

Yuhuai Wu, Albert Q. Jiang, Jimmy Ba, Roger Baker Grosse

Proceedings of the 9th International Conference on Learning Representations, 2021

IsarStep: a Benchmark for High-level Mathematical Reasoning.

Wenda Li, Lei Yu, Yuhuai Wu, Lawrence C. Paulson

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Branching Heuristics for Propositional Model Counting.

Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu, Chris J. Maddison, Roger B. Grosse, Sanjit A. Seshia, Fahiem Bacchus

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning.

Yuhuai Wu, Honghua Dong, Roger B. Grosse, Jimmy Ba

CoRR, 2020

Learning Branching Heuristics for Propositional Model Counting.

Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu, Chris J. Maddison, Roger B. Grosse, Edward A. Lee, Sanjit A. Seshia, Fahiem Bacchus

CoRR, 2020

Modelling High-Level Mathematical Reasoning in Mechanised Declarative Proofs.

Wenda Li, Lei Yu, Yuhuai Wu, Lawrence C. Paulson

CoRR, 2020

OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning.

Alexander Vezhnevets, Yuhuai Wu, Maria K. Eckstein, Rémi Leblond, Joel Z. Leibo

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Grandmaster level in StarCraft II using multi-agent reinforcement learning.

Oriol Vinyals, Igor Babuschkin, Wojciech M. Czarnecki, Michaël Mathieu, Andrew Dudzik, Junyoung Chung, David H. Choi, Richard Powell, Timo Ewalds, Petko Georgiev, Junhyuk Oh, Dan Horgan, Manuel Kroiss, Ivo Danihelka, Aja Huang, Laurent Sifre, Trevor Cai, John P. Agapiou, Max Jaderberg, Alexander Sasha Vezhnevets, Rémi Leblond, Tobias Pohlen, Valentin Dalibard, David Budden, Yury Sulsky, James Molloy, Tom Le Paine, Çaglar Gülçehre, Ziyu Wang, Tobias Pfaff, Yuhuai Wu, Roman Ring, Dani Yogatama, Dario Wünsch, Katrina McKinney, Oliver Smith, Tom Schaul, Timothy P. Lillicrap, Koray Kavukcuoglu, Demis Hassabis, Chris Apps, David Silver

Nat., 2019

Options as responses: Grounding behavioural hierarchies in multi-agent RL.

Alexander Sasha Vezhnevets, Yuhuai Wu, Rémi Leblond, Joel Z. Leibo

CoRR, 2019

Concurrent Meta Reinforcement Learning.

Emilio Parisotto, Soham Ghosh, Sai Bhargav Yalamanchi, Varsha Chinnaobireddy, Yuhuai Wu, Ruslan Salakhutdinov

CoRR, 2019

ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning.

Harris Chan, Yuhuai Wu, Jamie Kiros, Sanja Fidler, Jimmy Ba

CoRR, 2019

2018

Some Considerations on Learning to Explore via Meta-Reinforcement Learning.

Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever

CoRR, 2018

An Empirical Analysis of Proximal Policy Optimization with Kronecker-factored Natural Gradients.

Jiaming Song, Yuhuai Wu

CoRR, 2018

The Importance of Sampling inMeta-Reinforcement Learning.

Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Understanding Short-Horizon Bias in Stochastic Meta-Optimization.

Yuhuai Wu, Mengye Ren, Renjie Liao, Roger B. Grosse

Proceedings of the 6th International Conference on Learning Representations, 2018

Backpropagation through the Void: Optimizing control variates for black-box gradient estimation.

Will Grathwohl, Dami Choi, Yuhuai Wu, Geoffrey Roeder, David Duvenaud

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

STDP-Compatible Approximation of Backpropagation in an Energy-Based Model.

Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhuai Wu

Neural Comput., 2017

Sticking the Landing: An Asymptotically Zero-Variance Gradient Estimator for Variational Inference.

Geoffrey Roeder, Yuhuai Wu, David Duvenaud

CoRR, 2017

Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation

Yuhuai Wu, Elman Mansimov, Roger B. Grosse, Shun Liao, Jimmy Ba

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference.

Geoffrey Roeder, Yuhuai Wu, David Duvenaud

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

On the Quantitative Analysis of Decoder-Based Generative Models.

Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger B. Grosse

Proceedings of the 5th International Conference on Learning Representations, 2017

2016

Architectural Complexity Measures of Recurrent Neural Networks.

Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

On Multiplicative Integration with Recurrent Neural Networks.

Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations.

Behnam Neyshabur, Yuhuai Wu, Ruslan Salakhutdinov, Nati Srebro

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016