Yuhuai Wu - RankMe

85 papers A* 26Journal 49Unranked 9

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Don't Trust: Verify - Grounding LLM Quantitative Reasoning with Autoformalization. ICLR Jin Peng Zhou, Charles Staats, Wenda Li, Christian Szegedy, Kilian Q. Weinberger, Yuhuai Wu
2024	J	`jnl`	Don't Trust: Verify - Grounding LLM Quantitative Reasoning with Autoformalization. CoRR Jin Peng Zhou, Charles Staats, Wenda Li, Christian Szegedy, Kilian Q. Weinberger, Yuhuai Wu
2024	A*	`conf`	Magnushammer: A Transformer-Based Approach to Premise Selection. ICLR Maciej Mikula, Szymon Tworkowski, Szymon Antoniak, Bartosz Piotrowski, Albert Q. Jiang, Jin Peng Zhou, Christian Szegedy, Lukasz Kucinski, Piotr Milos, Yuhuai Wu
2024	J	`jnl`	Meta-Designing Quantum Experiments with Language Models. CoRR Sören Arlt, Haonan Duan, Felix Li, Sang Michael Xie, Yuhuai Wu, Mario Krenn
2024	—	`—`	Neural Networks for Mathematical Reasoning - Evaluations, Capabilities, and Techniques Yuhuai Wu
2024	A*	`conf`	REFACTOR: Learning to Extract Theorems from Proofs. ICLR Jin Peng Zhou, Yuhuai Wu, Qiyang Li, Roger Baker Grosse
2024	J	`jnl`	REFACTOR: Learning to Extract Theorems from Proofs. CoRR Jin Peng Zhou, Yuhuai Wu, Qiyang Li, Roger B. Grosse
2024	J	`jnl`	Solving olympiad geometry without human demonstrations. Nat. Trieu H. Trinh, Yuhuai Wu, Quoc V. Le, He He, Thang Luong
2023	A*	`conf`	Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs. ICLR Albert Qiaochu Jiang, Sean Welleck, Jin Peng Zhou, Timothée Lacroix, Jiacheng Liu, Wenda Li, Mateja Jamnik, Guillaume Lample, Yuhuai Wu
2023	J	`jnl`	Evaluating Language Models for Mathematics through Interactions. CoRR 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
2023	A*	`conf`	Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search. ICLR Michal Zawalski, Michal Tyrolski, Konrad Czechowski, Tomasz Odrzygózdz, Damian Stachura, Piotr Piekos, Yuhuai Wu, Lukasz Kucinski, Piotr Milos
2023	A*	`conf`	Focused Transformer: Contrastive Training for Context Scaling. NeurIPS Szymon Tworkowski, Konrad Staniszewski, Mikolaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Milos
2023	J	`jnl`	Focused Transformer: Contrastive Training for Context Scaling. CoRR Szymon Tworkowski, Konrad Staniszewski, Mikolaj Pacek, Yuhuai Wu, Henryk Michalewski, Piotr Milos
2023	J	`jnl`	Holistic Evaluation of Language Models. Trans. Mach. Learn. Res. 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
2023	J	`jnl`	Length Generalization in Arithmetic Transformers. CoRR Samy Jelassi, Stéphane d'Ascoli, Carles Domingo-Enrich, Yuhuai Wu, Yuanzhi Li, François Charton
2023	A*	`conf`	Lexinvariant Language Models. NeurIPS Qian Huang, Eric Zelikman, Sarah Li Chen, Yuhuai Wu, Gregory Valiant, Percy Liang
2023	J	`jnl`	Lexinvariant Language Models. CoRR Qian Huang, Eric Zelikman, Sarah Li Chen, Yuhuai Wu, Gregory Valiant, Percy Liang
2023	J	`jnl`	Magnushammer: A Transformer-based Approach to Premise Selection. CoRR Maciej Mikula, Szymon Antoniak, Szymon Tworkowski, Albert Qiaochu Jiang, Jin Peng Zhou, Christian Szegedy, Lukasz Kucinski, Piotr Milos, Yuhuai Wu
2022	A*	`conf`	Autoformalization with Large Language Models. NeurIPS Yuhuai Wu, Albert Qiaochu Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy
2022	J	`jnl`	Autoformalization with Large Language Models. CoRR Yuhuai Wu, Albert Q. Jiang, Wenda Li, Markus N. Rabe, Charles Staats, Mateja Jamnik, Christian Szegedy
2022	A*	`conf`	Block-Recurrent Transformers. NeurIPS DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, Behnam Neyshabur
2022	J	`jnl`	Block-Recurrent Transformers. CoRR DeLesley Hutchins, Imanol Schlag, Yuhuai Wu, Ethan Dyer, Behnam Neyshabur
2022	J	`jnl`	Draft, Sketch, and Prove: Guiding Formal Theorem Provers with Informal Proofs. CoRR Albert Q. Jiang, Sean Welleck, Jin Peng Zhou, Wenda Li, Jiacheng Liu, Mateja Jamnik, Timothée Lacroix, Yuhuai Wu, Guillaume Lample
2022	A*	`conf`	Exploring Length Generalization in Large Language Models. NeurIPS Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra, Vinay V. Ramasesh, Ambrose Slone, Guy Gur-Ari, Ethan Dyer, Behnam Neyshabur
2022	J	`jnl`	Exploring Length Generalization in Large Language Models. CoRR Cem Anil, Yuhuai Wu, Anders Andreassen, Aitor Lewkowycz, Vedant Misra, Vinay V. Ramasesh, Ambrose Slone, Guy Gur-Ari, Ethan Dyer, Behnam Neyshabur
2022	J	`jnl`	Fast and Precise: Adjusting Planning Horizon with Adaptive Subgoal Search. CoRR Michal Zawalski, Michal Tyrolski, Konrad Czechowski, Damian Stachura, Piotr Piekos, Tomasz Odrzygózdz, Yuhuai Wu, Lukasz Kucinski, Piotr Milos
2022	—	`conf`	Hierarchical Transformers Are More Efficient Language Models. NAACL-HLT (Findings) Piotr Nawrot, Szymon Tworkowski, Michal Tyrolski, Lukasz Kaiser, Yuhuai Wu, Christian Szegedy, Henryk Michalewski
2022	J	`jnl`	Holistic Evaluation of Language Models. CoRR 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
2022	A*	`conf`	Insights into Pre-training via Simpler Synthetic Tasks. NeurIPS Yuhuai Wu, Felix Li, Percy Liang
2022	J	`jnl`	Insights into Pre-training via Simpler Synthetic Tasks. CoRR Yuhuai Wu, Felix Li, Percy Liang
2022	A*	`conf`	Invariant Causal Representation Learning for Out-of-Distribution Generalization. ICLR Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf
2022	J	`jnl`	Language Model Cascades. CoRR 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
2022	A*	`conf`	Memorizing Transformers. ICLR Yuhuai Wu, Markus Norman Rabe, DeLesley Hutchins, Christian Szegedy
2022	J	`jnl`	Memorizing Transformers. CoRR Yuhuai Wu, Markus N. Rabe, DeLesley Hutchins, Christian Szegedy
2022	A*	`conf`	Path Independent Equilibrium Models Can Better Exploit Test-Time Computation. NeurIPS Cem Anil, Ashwini Pokle, Kaiqu Liang, Johannes Treutlein, Yuhuai Wu, Shaojie Bai, J. Zico Kolter, Roger B. Grosse
2022	J	`jnl`	Path Independent Equilibrium Models Can Better Exploit Test-Time Computation. CoRR Cem Anil, Ashwini Pokle, Kaiqu Liang, Johannes Treutlein, Yuhuai Wu, Shaojie Bai, Zico Kolter, Roger B. Grosse
2022	A*	`conf`	Proof Artifact Co-Training for Theorem Proving with Language Models. ICLR Jesse Michael Han, Jason Rute, Yuhuai Wu, Edward W. Ayers, Stanislas Polu
2022	A*	`conf`	STaR: Bootstrapping Reasoning With Reasoning. NeurIPS Eric Zelikman, Yuhuai Wu, Jesse Mu, Noah D. Goodman
2022	J	`jnl`	STaR: Bootstrapping Reasoning With Reasoning. CoRR Eric Zelikman, Yuhuai Wu, Noah D. Goodman
2022	A*	`conf`	Solving Quantitative Reasoning Problems with Language Models. NeurIPS 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
2022	J	`jnl`	Solving Quantitative Reasoning Problems with Language Models. CoRR 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
2022	A*	`conf`	Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers. NeurIPS Albert Qiaochu Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygózdz, Piotr Milos, Yuhuai Wu, Mateja Jamnik
2022	J	`jnl`	Thor: Wielding Hammers to Integrate Language Models and Automated Theorem Provers. CoRR Albert Q. Jiang, Wenda Li, Szymon Tworkowski, Konrad Czechowski, Tomasz Odrzygózdz, Piotr Milos, Yuhuai Wu, Mateja Jamnik
2021	J	`jnl`	Discrete Equidecomposability and Ehrhart Theory of Polygons. Discret. Comput. Geom. Paxton Turner, Yuhuai Wu
2021	A*	`conf`	Efficient Statistical Tests: A Neural Tangent Kernel Approach. ICML Sheng Jia, Ehsan Nezhadarya, Yuhuai Wu, Jimmy Ba
2021	J	`jnl`	Hierarchical Transformers Are More Efficient Language Models. CoRR Piotr Nawrot, Szymon Tworkowski, Michal Tyrolski, Lukasz Kaiser, Yuhuai Wu, Christian Szegedy, Henryk Michalewski
2021	A*	`conf`	INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving. ICLR Yuhuai Wu, Albert Q. Jiang, Jimmy Ba, Roger Baker Grosse
2021	A*	`conf`	IsarStep: a Benchmark for High-level Mathematical Reasoning. ICLR Wenda Li, Lei Yu, Yuhuai Wu, Lawrence C. Paulson
2021	A*	`conf`	LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. ICML Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy
2021	J	`jnl`	LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning. CoRR Yuhuai Wu, Markus N. Rabe, Wenda Li, Jimmy Ba, Roger B. Grosse, Christian Szegedy
2021	A*	`conf`	Learning Branching Heuristics for Propositional Model Counting. AAAI Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu, Chris J. Maddison, Roger B. Grosse, Sanjit A. Seshia, Fahiem Bacchus
2021	J	`jnl`	Learning to Give Checkable Answers with Prover-Verifier Games. CoRR Cem Anil, Guodong Zhang, Yuhuai Wu, Roger B. Grosse
2021	J	`jnl`	Nonlinear Invariant Risk Minimization: A Causal Approach. CoRR Chaochao Lu, Yuhuai Wu, José Miguel Hernández-Lobato, Bernhard Schölkopf
2021	J	`jnl`	Proof Artifact Co-training for Theorem Proving with Language Models. CoRR Jesse Michael Han, Jason Rute, Yuhuai Wu, Edward W. Ayers, Stanislas Polu
2021	A*	`conf`	Subgoal Search For Complex Reasoning Tasks. NeurIPS Konrad Czechowski, Tomasz Odrzygózdz, Marek Zbysinski, Michal Zawalski, Krzysztof Olejnik, Yuhuai Wu, Lukasz Kucinski, Piotr Milos
2021	J	`jnl`	Subgoal Search For Complex Reasoning Tasks. CoRR Konrad Czechowski, Tomasz Odrzygózdz, Marek Zbysinski, Michal Zawalski, Krzysztof Olejnik, Yuhuai Wu, Lukasz Kucinski, Piotr Milos
2020	J	`jnl`	INT: An Inequality Benchmark for Evaluating Generalization in Theorem Proving. CoRR Yuhuai Wu, Albert Q. Jiang, Jimmy Ba, Roger B. Grosse
2020	J	`jnl`	Learning Branching Heuristics for Propositional Model Counting. CoRR Pashootan Vaezipoor, Gil Lederman, Yuhuai Wu, Chris J. Maddison, Roger B. Grosse, Edward A. Lee, Sanjit A. Seshia, Fahiem Bacchus
2020	J	`jnl`	Modelling High-Level Mathematical Reasoning in Mechanised Declarative Proofs. CoRR Wenda Li, Lei Yu, Yuhuai Wu, Lawrence C. Paulson
2020	A*	`conf`	OPtions as REsponses: Grounding behavioural hierarchies in multi-agent reinforcement learning. ICML Alexander Vezhnevets, Yuhuai Wu, Maria K. Eckstein, Rémi Leblond, Joel Z. Leibo
2020	J	`jnl`	The Scattering Compositional Learner: Discovering Objects, Attributes, Relationships in Analogical Reasoning. CoRR Yuhuai Wu, Honghua Dong, Roger B. Grosse, Jimmy Ba
2019	J	`jnl`	ACTRCE: Augmenting Experience via Teacher's Advice For Multi-Goal Reinforcement Learning. CoRR Harris Chan, Yuhuai Wu, Jamie Kiros, Sanja Fidler, Jimmy Ba
2019	J	`jnl`	Concurrent Meta Reinforcement Learning. CoRR Emilio Parisotto, Soham Ghosh, Sai Bhargav Yalamanchi, Varsha Chinnaobireddy, Yuhuai Wu, Ruslan Salakhutdinov
2019	J	`jnl`	Grandmaster level in StarCraft II using multi-agent reinforcement learning. Nat. 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
2019	J	`jnl`	Options as responses: Grounding behavioural hierarchies in multi-agent RL. CoRR Alexander Sasha Vezhnevets, Yuhuai Wu, Rémi Leblond, Joel Z. Leibo
2018	J	`jnl`	An Empirical Analysis of Proximal Policy Optimization with Kronecker-factored Natural Gradients. CoRR Jiaming Song, Yuhuai Wu
2018	—	`conf`	Backpropagation through the Void: Optimizing control variates for black-box gradient estimation. ICLR (Poster) Will Grathwohl, Dami Choi, Yuhuai Wu, Geoffrey Roeder, David Duvenaud
2018	J	`jnl`	Some Considerations on Learning to Explore via Meta-Reinforcement Learning. CoRR Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever
2018	A*	`conf`	The Importance of Sampling inMeta-Reinforcement Learning. NeurIPS Bradly C. Stadie, Ge Yang, Rein Houthooft, Xi Chen, Yan Duan, Yuhuai Wu, Pieter Abbeel, Ilya Sutskever
2018	—	`conf`	Understanding Short-Horizon Bias in Stochastic Meta-Optimization. ICLR (Poster) Yuhuai Wu, Mengye Ren, Renjie Liao, Roger B. Grosse
2018	J	`jnl`	Understanding Short-Horizon Bias in Stochastic Meta-Optimization. CoRR Yuhuai Wu, Mengye Ren, Renjie Liao, Roger B. Grosse
2017	J	`jnl`	Backpropagation through the Void: Optimizing control variates for black-box gradient estimation. CoRR Will Grathwohl, Dami Choi, Yuhuai Wu, Geoffrey Roeder, David Duvenaud
2017	—	`conf`	On the Quantitative Analysis of Decoder-Based Generative Models. ICLR (Poster) Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger B. Grosse
2017	J	`jnl`	STDP-Compatible Approximation of Backpropagation in an Energy-Based Model. Neural Comput. Yoshua Bengio, Thomas Mesnard, Asja Fischer, Saizheng Zhang, Yuhuai Wu
2017	—	`conf`	Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation NIPS Yuhuai Wu, Elman Mansimov, Roger B. Grosse, Shun Liao, Jimmy Ba
2017	J	`jnl`	Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation. CoRR Yuhuai Wu, Elman Mansimov, Shun Liao, Roger B. Grosse, Jimmy Ba
2017	J	`jnl`	Sticking the Landing: An Asymptotically Zero-Variance Gradient Estimator for Variational Inference. CoRR Geoffrey Roeder, Yuhuai Wu, David Duvenaud
2017	—	`conf`	Sticking the Landing: Simple, Lower-Variance Gradient Estimators for Variational Inference. NIPS Geoffrey Roeder, Yuhuai Wu, David Duvenaud
2016	—	`conf`	Architectural Complexity Measures of Recurrent Neural Networks. NIPS Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio
2016	J	`jnl`	Architectural Complexity Measures of Recurrent Neural Networks. CoRR Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio
2016	—	`conf`	On Multiplicative Integration with Recurrent Neural Networks. NIPS Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov
2016	J	`jnl`	On Multiplicative Integration with Recurrent Neural Networks. CoRR Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov
2016	J	`jnl`	On the Quantitative Analysis of Decoder-Based Generative Models. CoRR Yuhuai Wu, Yuri Burda, Ruslan Salakhutdinov, Roger B. Grosse
2016	—	`conf`	Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations. NIPS Behnam Neyshabur, Yuhuai Wu, Ruslan Salakhutdinov, Nati Srebro
2016	J	`jnl`	Path-Normalized Optimization of Recurrent Neural Networks with ReLU Activations. CoRR Behnam Neyshabur, Yuhuai Wu, Ruslan Salakhutdinov, Nathan Srebro