Yuhuai Wu

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All published works

Action	Title	Year	Authors
+ PDF Chat	Evaluating language models for mathematics through interactions	2024	Katherine M. Collins Albert Q. Jiang Simon Frieder Lionel Wong Miri Zilka Umang Bhatt Thomas Lukasiewicz Yuhuai Wu Joshua B. Tenenbaum William Hart
+ PDF Chat	Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization	2024	Jin Zhou Charles Staats Wenda Li Christian Szegedy Kilian Q. Weinberger Yuhuai Wu
+ PDF Chat	REFACTOR: Learning to Extract Theorems from Proofs	2024	Jin Zhou Yuhuai Wu Qiyang Li Roger Grosse
+	Magnushammer: A Transformer-based Approach to Premise Selection	2023	Maciej Mikuła Szymon Antoniak Szymon Tworkowski Albert Qiaochu Jiang Jin Zhou Christian Szegedy Łukasz Kuciński Piotr Miłoś Yuhuai Wu
+	PaLM 2 Technical Report	2023	Rohan Anil Andrew M. Dai Orhan Fırat Melvin Johnson Dmitry Lepikhin A. M. A. dos Passos Siamak Shakeri Emanuel Taropa Paige Bailey Zhifeng Chen
+	Lexinvariant Language Models	2023	Qian Huang Eric Zelikman Sarah Li Chen Yuhuai Wu Gregory Valiant Percy Liang
+	Evaluating Language Models for Mathematics through Interactions	2023	Katherine M. Collins Albert Q. Jiang Simon Frieder Lionel Wong Miri Zilka Umang Bhatt Thomas Lukasiewicz Yuhuai Wu Joshua B. Tenenbaum William E. Hart
+	Length Generalization in Arithmetic Transformers	2023	Samy Jelassi Stéphane d’Ascoli Carles Domingo-Enrich Yuhuai Wu Yuanzhi Li François Charton
+	Focused Transformer: Contrastive Training for Context Scaling	2023	Szymon Tworkowski Konrad Staniszewski Mikołaj Pacek Yuhuai Wu Henryk Michalewski Piotr Miłoś
+ PDF Chat	Hierarchical Transformers Are More Efficient Language Models	2022	Piotr Nawrot Szymon Tworkowski Michał Tyrolski Łukasz Kaiser Yuhuai Wu Christian Szegedy Henryk Michalewski
+	Memorizing Transformers	2022	Yuhuai Wu Markus N. Rabe DeLesley Hutchins Christian Szegedy
+	Block-Recurrent Transformers	2022	DeLesley Hutchins Imanol Schlag Yuhuai Wu Ethan Dyer Behnam Neyshabur
+	STaR: Bootstrapping Reasoning With Reasoning	2022	Eric Zelikman Yuhuai Wu Noah D. Goodman
+	Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers	2022	Albert Q. Jiang Wenda Li Szymon Tworkowski Konrad Czechowski Tomasz Odrzygóźdź Piotr Miłoś Yuhuai Wu Mateja Jamnik
+	Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search	2022	Michał Zawalski Michał Tyrolski Konrad Czechowski Damian Stachura Piotr Piękos Tomasz Odrzygóźdź Yuhuai Wu Łukasz Kuciński Piotr Miłoś
+	Autoformalization with Large Language Models	2022	Yuhuai Wu Albert Q. Jiang Wenda Li Markus N. Rabe Charles Staats Mateja Jamnik Christian Szegedy
+	Insights into Pre-training via Simpler Synthetic Tasks	2022	Yuhuai Wu Felix Li Percy Liang
+	Solving Quantitative Reasoning Problems with Language Models	2022	Aitor Lewkowycz Anders Andreassen David Dohan Ethan Dyer Henryk Michalewski Vinay Ramasesh Ambrose Slone Cem Anil Imanol Schlag Theo Gutman-Solo
+	Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs	2022	Albert Q. Jiang Sean Welleck Jin Zhou Wenda Li Jiacheng Liu Mateja Jamnik Timothée Lacroix Yuhuai Wu Guillaume Lample
+	Path Independent Equilibrium Models Can Better Exploit Test-Time Computation	2022	Cem Anil Ashwini Pokle Kaiqu Liang Johannes Treutlein Yuhuai Wu Shaojie Bai Zico Kolter Roger Grosse
+	Holistic Evaluation of Language Models	2022	Percy Liang Rishi Bommasani Tong Lee Dimitris Tsipras Dilara Soylu Michihiro Yasunaga Yian Zhang Deepak Narayanan Yuhuai Wu Ananya Kumar
+	Exploring Length Generalization in Large Language Models	2022	Cem Anil Yuhuai Wu Anders Andreassen Aitor Lewkowycz Vedant Misra Vinay Ramasesh Ambrose Slone Guy Gur-Ari Ethan Dyer Behnam Neyshabur
+	Language Model Cascades	2022	David Dohan Winnie Xu Aitor Lewkowycz Jacob Austin David Bieber Raphael Gontijo Lopes Yuhuai Wu Henryk Michalewski Rif A. Saurous Jascha Sohl‐Dickstein
+	Subgoal Search For Complex Reasoning Tasks	2021	Konrad Czechowski Tomasz Odrzygóźdź Marek Zbysiński Michał Zawalski Krzysztof Olejnik Yuhuai Wu Łukasz Kuciński Piotr Miłoś
+	Learning to Give Checkable Answers with Prover-Verifier Games.	2021	Cem Anil Guodong Zhang Yuhuai Wu Roger Grosse
+	Subgoal Search For Complex Reasoning Tasks	2021	Konrad Czechowski Tomasz Odrzygóźdź Marek Zbysiński Michał Zawalski Krzysztof Olejnik Yuhuai Wu Łukasz Kuciński Piotr Miłoś
+ PDF Chat	Learning Branching Heuristics for Propositional Model Counting	2021	Pashootan Vaezipoor Gil Lederman Yuhuai Wu Chris J. Maddison Roger Grosse Sanjit A. Seshia Fahiem Bacchus
+	INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving	2021	Yuhuai Wu Albert Qiaochu Jiang Jimmy Ba Roger Grosse
+	Proof Artifact Co-training for Theorem Proving with Language Models.	2021	Jesse Michael Han Jason Rute Yuhuai Wu Edward W. Ayers Stanislas Polu
+	LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning.	2021	Yuhuai Wu Markus N. Rabe Wenda Li Jimmy Ba Roger Grosse Christian Szegedy
+ PDF Chat	LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning	2021	Yuhuai Wu Markus Rabe Wenda Li Jimmy Ba Roger Grosse Christian Szegedy
+	Nonlinear Invariant Risk Minimization: A Causal Approach	2021	Chaochao Lu Yuhuai Wu José Miguel Hernández-Lobato Bernhard Schölkopf
+	LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning	2021	Yuhuai Wu Markus N. Rabe Wenda Li Jimmy Ba Roger Grosse Christian Szegedy
+	On the Opportunities and Risks of Foundation Models	2021	Rishi Bommasani Drew A. Hudson Ehsan Adeli Russ B. Altman Simran Arora Sydney von Arx Michael S. Bernstein Jeannette Bohg Antoine Bosselut Emma Brunskill
+	Hierarchical Transformers Are More Efficient Language Models	2021	Piotr Nawrot Szymon Tworkowski Michał Tyrolski Łukasz Kaiser Yuhuai Wu Christian Szegedy Henryk Michalewski
+	Learning to Give Checkable Answers with Prover-Verifier Games	2021	Cem Anil Guodong Zhang Yuhuai Wu Roger Grosse
+	Subgoal Search For Complex Reasoning Tasks	2021	Konrad Czechowski Tomasz Odrzygóźdź Marek Zbysiński Michał Zawalski Krzysztof Olejnik Yuhuai Wu Łukasz Kuciński Piotr Miłoś
+	Proof Artifact Co-training for Theorem Proving with Language Models	2021	Jesse Michael Han Jason Rute Yuhuai Wu Edward W. Ayers Stanislas Polu
+	Learning Branching Heuristics for Propositional Model Counting	2020	Pashootan Vaezipoor Gil Lederman Yuhuai Wu Chris J. Maddison Roger Grosse Edward A. Lee Sanjit A. Seshia Fahiem Bacchus
+	Modelling High-Level Mathematical Reasoning in Mechanised Declarative Proofs	2020	Wenda Li Yu Lei Yuhuai Wu Lawrence C. Paulson
+ PDF Chat	Discrete Equidecomposability and Ehrhart Theory of Polygons	2020	Paxton Turner Yuhuai Wu
+	INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving	2020	Yuhuai Wu Albert Qiaochu Jiang Jimmy Ba Roger Grosse
+	The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning	2020	Yuhuai Wu Honghua Dong Roger Grosse Jimmy Ba
+	IsarStep: a Benchmark for High-level Mathematical Reasoning	2020	Wenda Li Lei Yu Yuhuai Wu Lawrence C. Paulson
+	Learning Branching Heuristics for Propositional Model Counting	2020	Pashootan Vaezipoor G. Lederman Yuhuai Wu Chris J. Maddison Roger Grosse Edward Lee Sanjit A. Seshia Fahiem Bacchus
+	ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning	2019	Harris Chan Yuhuai Wu Jamie Kiros Sanja Fidler Jimmy Ba
+	Concurrent Meta Reinforcement Learning	2019	Emilio Parisotto Soham Ghosh Sai Yalamanchi Varsha Chinnaobireddy Yuhuai Wu Ruslan Salakhutdinov
+	Options as responses: Grounding behavioural hierarchies in multi-agent RL	2019	Alexander Sasha Vezhnevets Yuhuai Wu Rémi Leblond Joel Z. Leibo
+	Understanding Short-Horizon Bias in Stochastic Meta-Optimization	2018	Yuhuai Wu Mengye Ren Renjie Liao Roger Grosse
+	An Empirical Analysis of Proximal Policy Optimization with Kronecker-factored Natural Gradients	2018	Jiaming Song Yuhuai Wu
+	Some Considerations on Learning to Explore via Meta-Reinforcement Learning	2018	Bradly C. Stadie Ge Yang Rein Houthooft Xi Chen Yan Duan Yuhuai Wu Pieter Abbeel Ilya Sutskever
+	Understanding Short-Horizon Bias in Stochastic Meta-Optimization	2018	Yuhuai Wu Mengye Ren Renjie Liao Roger Grosse
+	Backpropagation through the Void: Optimizing control variates for black-box gradient estimation	2017	Will Grathwohl Dami Choi Yuhuai Wu Geoffrey Roeder David Duvenaud
+	Sticking the Landing: An Asymptotically Zero-Variance Gradient Estimator for Variational Inference.	2017	Geoffrey Roeder Yuhuai Wu David Duvenaud
+	Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference	2017	Geoffrey Roeder Yuhuai Wu David Duvenaud
+	Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation	2017	Yuhuai Wu Elman Mansimov S. Matthew Liao Roger Grosse Jimmy Ba
+	Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference	2017	Geoffrey Roeder Yuhuai Wu David Duvenaud
+	Backpropagation through the Void: Optimizing control variates for black-box gradient estimation	2017	Will Grathwohl Dami Choi Yuhuai Wu Geoffrey Roeder David Duvenaud
+	On Multiplicative Integration with Recurrent Neural Networks	2016	Yuhuai Wu Saizheng Zhang Ying Zhang Yoshua Bengio Ruslan Salakhutdinov
+	Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations	2016	Behnam Neyshabur Yuhuai Wu Ruslan Salakhutdinov Nathan Srebro
+	Architectural Complexity Measures of Recurrent Neural Networks	2016	Saizheng Zhang Yuhuai Wu Tong Che Zhouhan Lin Roland Memisevic Ruslan Salakhutdinov Yoshua Bengio
+	On the Quantitative Analysis of Decoder-Based Generative Models	2016	Yuhuai Wu Yuri Burda Ruslan Salakhutdinov Roger Grosse
+	On Multiplicative Integration with Recurrent Neural Networks	2016	Yuhuai Wu Saizheng Zhang Ying Zhang Yoshua Bengio Russ R. Salakhutdinov
+	Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations	2016	Behnam Neyshabur Yuhuai Wu Ruslan Salakhutdinov Nathan Srebro
+	Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations	2016	Behnam Neyshabur Yuhuai Wu Ruslan Salakhutdinov Nathan Srebro
+	STDP as presynaptic activity times rate of change of postsynaptic activity	2015	Yoshua Bengio Thomas Mesnard Asja Fischer Saizheng Zhang Yuhuai Wu
+	Discrete Equidecomposability and Ehrhart Theory of Polygons	2014	Paxton Turner Yuhuai Wu
+	Conditions for Discrete Equidecomposability of Polygons	2014	Paxton Turner Yuhuai Wu
+	Discrete Equidecomposability and Ehrhart Theory of Polygons	2014	Paxton Turner Yuhuai Wu
+	Estimation and testing in an imperfect-inspection model	1993	Muni S. Srivastava Yuhuai Wu

Common Coauthors

Coauthor	Papers Together
Roger Grosse	17
Christian Szegedy	9
Jimmy Ba	8
Ruslan Salakhutdinov	7
Piotr Miłoś	7
Behnam Neyshabur	6
Wenda Li	6
Łukasz Kuciński	5
Geoffrey Roeder	5
Mateja Jamnik	5
Konrad Czechowski	5
Albert Q. Jiang	5
Wenda Li	5
Cem Anil	5
Henryk Michalewski	5
David Duvenaud	5
Ethan Dyer	4
Percy Liang	4
Yoshua Bengio	4
Michał Zawalski	4
Markus N. Rabe	4
Paxton Turner	4
Saizheng Zhang	4
Jin Zhou	4
Albert Qiaochu Jiang	3
Marek Zbysiński	3
Ambrose Slone	3
Pashootan Vaezipoor	3
Tomasz Odrzygóźdź	3
Fahiem Bacchus	3
Guy Gur-Ari	3
Sanjit A. Seshia	3
Nathan Srebro	3
Chris J. Maddison	3
Michał Tyrolski	3
Aitor Lewkowycz	3
W. T. Gowers	2
Piotr Nawrot	2
Renjie Liao	2
Tomasz Odrzygóźdź	2
Noah D. Goodman	2
Christopher D. Manning	2
Peter Henderson	2
Will Grathwohl	2
Benjamin T. Newman	2
Łukasz Kaiser	2
Vedant Misra	2
Niladri S. Chatterji	2
Adrian Weller	2
Dami Choi	2

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	10
+	Generative Language Modeling for Automated Theorem Proving.	2020	Stanislas Polu Ilya Sutskever	8
+	Language Models are Few-Shot Learners	2020	T. B. Brown Benjamin Mann Nick Ryder Melanie Subbiah Jared Kaplan Prafulla Dhariwal Arvind Neelakantan Pranav Shyam Girish Sastry Amanda Askell	6
+	Attention is All you Need	2017	Ashish Vaswani Noam Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan N. Gomez Łukasz Kaiser Illia Polosukhin	6
+	INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving	2021	Yuhuai Wu Albert Qiaochu Jiang Jimmy Ba Roger Grosse	5
+ PDF Chat	First Neural Conjecturing Datasets and Experiments	2020	Josef Urban Jan Jakubův	5
+	Neural Machine Translation by Jointly Learning to Align and Translate	2015	Dzmitry Bahdanau Kyunghyun Cho Yoshua Bengio	4
+	The minimum period of the Ehrhart quasi-polynomial of a rational polytope	2004	Tyrrell B. McAllister Kevin M. Woods	4
+ PDF Chat	TacticToe: Learning to Reason with HOL4 Tactics	2018	Thibault Gauthier Cezary Kaliszyk Josef Urban	4
+	Asynchronous Methods for Deep Reinforcement Learning	2016	Volodymyr Mnih Adrià Puigdomènech Badia Mehdi Mirza Alex Graves Tim Harley Timothy Lillicrap David Silver Koray Kavukcuoglu	4
+ PDF Chat	fairseq: A Fast, Extensible Toolkit for Sequence Modeling	2019	Myle Ott Sergey Edunov Alexei Baevski Angela Fan Sam Gross Nathan Ng David Grangier Michael Auli	4
+	Stochastic Backpropagation and Approximate Inference in Deep Generative Models	2014	Danilo Jimenez Rezende Shakir Mohamed Daan Wierstra	4
+	How Powerful are Graph Neural Networks?	2018	Keyulu Xu Weihua Hu Jure Leskovec Stefanie Jegelka	4
+	Piecewise SL 2 Z Geometry	1993	Peter Greenberg	3
+	Modelling High-Level Mathematical Reasoning in Mechanised Declarative Proofs	2020	Wenda Li Yu Lei Yuhuai Wu Lawrence C. Paulson	3
+	Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation	2017	Yuhuai Wu Elman Mansimov S. Matthew Liao Roger Grosse Jimmy Ba	3
+	Learning to Prove with Tactics	2018	Thibault Gauthier Cezary Kaliszyk Josef Urban Ramana Kumar Michael Norrish	3
+	Proximal Policy Optimization Algorithms	2017	John Schulman Filip Wolski Prafulla Dhariwal Alec Radford Oleg Klimov	3
+	On the Littlewood–Richardson polynomials	2002	Harm Derksen Jerzy Weyman	3
+ PDF Chat	The Bethe Ansatz and the combinatorics of Young tableaux	1988	A. N. Kirillov Nicolai Reshetikhin	3
+	Algebraic topology	2001	Allen Hatcher	3
+ PDF Chat	CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning	2017	Justin Johnson Bharath Hariharan Laurens van der Maaten Li Fei-Fei C. Lawrence Zitnick Ross Girshick	3
+ PDF Chat	Graph Representations for Higher-Order Logic and Theorem Proving	2020	Aditya Paliwal Sarah M. Loos Markus N. Rabe Kshitij Bansal Christian Szegedy	3
+	Evolution Strategies as a Scalable Alternative to Reinforcement Learning	2017	Tim Salimans Jonathan Ho Xi Chen Ilya Sutskever	3
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	3
+ PDF Chat	A FORMAL PROOF OF THE KEPLER CONJECTURE	2017	Thomas Hales Mark Adams Gertrud Bauer TAT DAT DANG John Harrison Hoang Le Truong Cezary Kaliszyk Victor Magron Sean McLaughlin TAT THANG NGUYEN	3
+	PyTorch: An Imperative Style, High-Performance Deep Learning Library	2019	Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury Gregory Chanan Trevor Killeen Zeming Lin Natalia Gimelshein Luca Antiga	3
+ PDF Chat	SQuAD: 100,000+ Questions for Machine Comprehension of Text	2016	Pranav Rajpurkar Jian Zhang Konstantin Lopyrev Percy Liang	3
+	Exploration of neural machine translation in autoformalization of mathematics in Mizar	2020	Qingxiang Wang Chad E. Brown Cezary Kaliszyk Josef Urban	3
+ PDF Chat	Vertices of Gelfand--Tsetlin Polytopes	2004	Jesús A. De Loera Tyrrell B. McAllister	3
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	3
+	Lattice invariant valuations on rational polytopes	1978	Peter McMullen	3
+ PDF Chat	Computing the continuous discretely: integer-point enumeration in polyhedra	2007	Matthias Beck Sinai Robins	3
+	Learning-assisted theorem proving with millions of lemmas	2014	Cezary Kaliszyk Josef Urban	3
+	Deep Learning for Symbolic Mathematics	2019	Guillaume Lample François Charton	3
+	Generating Long Sequences with Sparse Transformers.	2019	Rewon Child Scott Gray Alec Radford Ilya Sutskever	2
+	MASS: Masked Sequence to Sequence Pre-training for Language Generation	2019	Kaitao Song Xu Tan Tao Qin Jianfeng Lu Tie‐Yan Liu	2
+	Fast Graph Representation Learning with PyTorch Geometric	2019	Matthias Fey Jan Eric Lenssen	2
+	Regularization and nonlinearities for neural language models: when are they needed?	2013	Marius Pachitariu Maneesh Sahani	2
+	A Model Counter's Guide to Probabilistic Systems	2019	Marcell Vazquez-Chanlatte Markus N. Rabe Sanjit A. Seshia	2
+	Learning to Reason in Large Theories without Imitation	2021	Kshitij Bansal Christian Szegedy Markus N. Rabe Sarah M. Loos Viktor Toman	2
+	Hindsight Experience Replay	2017	Marcin Andrychowicz Filip Wolski Alex Ray Jonas Schneider Rachel Fong Peter Welinder Bob McGrew Josh Tobin Pieter Abbeel Wojciech Zaremba	2
+	A Simple Way to Initialize Recurrent Networks of Rectified Linear Units	2015	Quoc V. Le Navdeep Jaitly Geoffrey E. Hinton	2
+	Representation Learning with Contrastive Predictive Coding	2018	Aäron van den Oord Yazhe Li Oriol Vinyals	2
+	Towards Finding Longer Proofs	2019	Zsolt Zombori Adrián Csiszárik Henryk Michalewski Cezary Kaliszyk Josef Urban	2
+	The Option-Critic Architecture	2016	Pierre‐Luc Bacon Jean Harb Doina Precup	2
+	RL$^2$: Fast Reinforcement Learning via Slow Reinforcement Learning	2016	Yan Duan John Schulman Xi Chen Peter L. Bartlett Ilya Sutskever Pieter Abbeel	2
+	DeepMath - Deep Sequence Models for Premise Selection	2016	Alex Alemi François Chollet Niklas Eén Geoffrey Irving Christian Szegedy Josef Urban	2
+	Generating Sequences With Recurrent Neural Networks	2013	Alex Graves	2
+	HolStep: A Machine Learning Dataset for Higher-order Logic Theorem Proving	2017	Cezary Kaliszyk François Chollet Christian Szegedy	2