Xuezhi Wang

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 83

Top Topics

Text Generation

Relational Data

Top Venues

Proc. VLDB Endow.

Publications

Tu Vu, Mohit Iyyer, Xuezhi Wang, Noah Constant, Jerry W. Wei, Jason Wei, Chris Tar, Yun-Hsuan Sung, Denny Zhou, Quoc V. Le, Thang Luong
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation. ACL (Findings) (2024)
Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou
Large Language Models as Tool Makers. ICLR (2024)
Xinyun Chen, Ryan A. Chi, Xuezhi Wang, Denny Zhou
Premise Order Matters in Reasoning with Large Language Models. CoRR (2024)
Yongchao Zhou, Uri Alon, Xinyun Chen, Xuezhi Wang, Rishabh Agarwal, Denny Zhou
Transformers Can Achieve Length Generalization But Not Robustly. CoRR (2024)
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen
Large Language Models as Optimizers. ICLR (2024)
Meng Song, Xuezhi Wang, Tanay Biradar, Yao Qin, Manmohan Chandraker
A Minimalist Prompt for Zero-Shot Policy Learning. CoRR (2024)
Xuezhi Wang, Denny Zhou
Chain-of-Thought Reasoning Without Prompting. CoRR (2024)
Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez
TEMPERA: Test-Time Prompt Editing via Reinforcement Learning. ICLR (2023)
Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen
Large Language Models as Optimizers. CoRR (2023)
Zhiqing Sun, Xuezhi Wang, Yi Tay, Yiming Yang, Denny Zhou
Recitation-Augmented Language Models. ICLR (2023)
Xinyun Chen, Renat Aksitov, Uri Alon, Jie Ren, Kefan Xiao, Pengcheng Yin, Sushant Prakash, Charles Sutton, Xuezhi Wang, Denny Zhou
Universal Self-Consistency for Large Language Model Generation. CoRR (2023)
Yi Tay, Mostafa Dehghani, Vinh Q. Tran, Xavier Garcia, Jason Wei, Xuezhi Wang, Hyung Won Chung, Dara Bahri, Tal Schuster, Huaixiu Steven Zheng, Denny Zhou, Neil Houlsby, Donald Metzler
UL2: Unifying Language Learning Paradigms. ICLR (2023)
Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. SaTML (2023)
Amanda Baughan, Allison Mercurio, Ariel Liu, Xuezhi Wang, Jilin Chen, Xiao Ma
A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures. CoRR (2023)
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou
Self-Consistency Improves Chain of Thought Reasoning in Language Models. ICLR (2023)
Jindong Gu, Ahmad Beirami, Xuezhi Wang, Alex Beutel, Philip H. S. Torr, Yao Qin
Towards Robust Prompts on Vision-Language Models. CoRR (2023)
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel
PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. 24 (2023)
Jiaxin Huang, Shixiang Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han
Large Language Models Can Self-Improve. EMNLP (2023)
Bailin Wang, Zi Wang, Xuezhi Wang, Yuan Cao, Rif A. Saurous, Yoon Kim
Grammar Prompting for Domain-Specific Language Generation with Large Language Models. NeurIPS (2023)
Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel
What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. CoRR (2023)
Amanda Baughan, Xuezhi Wang, Ariel Liu, Allison Mercurio, Jilin Chen, Xiao Ma
A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures. CHI (2023)
Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel
Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. CoRR (2023)
Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou
Large Language Models as Tool Makers. CoRR (2023)
Albert Lu, Hongxin Zhang, Yanzhe Zhang, Xuezhi Wang, Diyi Yang
Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints. EACL (Findings) (2023)
Albert Lu, Hongxin Zhang, Yanzhe Zhang, Xuezhi Wang, Diyi Yang
Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints. CoRR (2023)
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR (2023)
Freda Shi, Mirac Suzgun, Markus Freitag, Xuezhi Wang, Suraj Srivats, Soroush Vosoughi, Hyung Won Chung, Yi Tay, Sebastian Ruder, Denny Zhou, Dipanjan Das, Jason Wei
Language models are multilingual chain-of-thought reasoners. ICLR (2023)
Tu Vu, Mohit Iyyer, Xuezhi Wang, Noah Constant, Jerry W. Wei, Jason Wei, Chris Tar, Yun-Hsuan Sung, Denny Zhou, Quoc V. Le, Thang Luong
FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation. CoRR (2023)
Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed H. Chi, Jilin Chen, Alex Beutel
Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. EMNLP (Findings) (2023)
Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez
TEMPERA: Test-Time Prompting via Reinforcement Learning. CoRR (2022)
Yanzhe Zhang, Xuezhi Wang, Diyi Yang
Continual Sequence Generation with Adaptive Compositional Modules. CoRR (2022)
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Sharan Narang, Gaurav Mishra, Adams Yu, Vincent Y. Zhao, Yanping Huang, Andrew M. Dai, Hongkun Yu, Slav Petrov, Ed H. Chi, Jeff Dean, Jacob Devlin, Adam Roberts, Denny Zhou, Quoc V. Le, Jason Wei
Scaling Instruction-Finetuned Language Models. CoRR (2022)
Zhiqing Sun, Xuezhi Wang, Yi Tay, Yiming Yang, Denny Zhou
Recitation-Augmented Language Models. CoRR (2022)
Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. NeurIPS (2022)
Xuezhi Wang, Haohan Wang, Diyi Yang
Measure and Improve Robustness in NLP Models: A Survey. NAACL-HLT (2022)
Jieyu Zhao, Xuezhi Wang, Yao Qin, Jilin Chen, Kai-Wei Chang
Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers. CoRR (2022)
Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. 23 (2022)
Yanzhe Zhang, Xuezhi Wang, Diyi Yang
Continual Sequence Generation with Adaptive Compositional Modules. ACL (1) (2022)
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou
Rationale-Augmented Ensembles in Language Models. CoRR (2022)
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed Chi, Quoc Le, Denny Zhou
Chain of Thought Prompting Elicits Reasoning in Large Language Models. CoRR (2022)
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. NeurIPS (2022)
Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han
Large Language Models Can Self-Improve. CoRR (2022)
Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi
Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. CoRR (2022)
Tianlu Wang, Rohit Sridhar, Diyi Yang, Xuezhi Wang
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models. NAACL-HLT (Findings) (2022)
Jieyu Zhao, Xuezhi Wang, Yao Qin, Jilin Chen, Kai-Wei Chang
Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers. EMNLP (Findings) (2022)
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou
Self-Consistency Improves Chain of Thought Reasoning in Language Models. CoRR (2022)
Freda Shi, Mirac Suzgun, Markus Freitag, Xuezhi Wang, Suraj Srivats, Soroush Vosoughi, Hyung Won Chung, Yi Tay, Sebastian Ruder, Denny Zhou, Dipanjan Das, Jason Wei
Language Models are Multilingual Chain-of-Thought Reasoners. CoRR (2022)
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, Noah Fiedel
PaLM: Scaling Language Modeling with Pathways. CoRR (2022)
Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang
Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. CoRR (2021)
Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi
Improving Calibration through the Relationship with Adversarial Robustness. NeurIPS (2021)
Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. KDD (2021)
Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information. CoRR (2021)
Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. AIES (2021)
Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. CoRR (2021)
Tianlu Wang, Diyi Yang, Xuezhi Wang
Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models. CoRR (2021)
Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
Measuring Recommender System Effects with Simulated Users. CoRR (2021)
Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. WSDM (2021)
Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. CoRR (2021)
Yufan Huang, Yanzhe Zhang, Jiaao Chen, Xuezhi Wang, Diyi Yang
Continual Learning for Text Classification with Information Disentanglement Based Regularization. CoRR (2021)
Xuezhi Wang, Haohan Wang, Diyi Yang
Measure and Improve Robustness in NLP Models: A Survey. CoRR (2021)
Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang
Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information. FAccT (2021)
Yufan Huang, Yanzhe Zhang, Jiaao Chen, Xuezhi Wang, Diyi Yang
Continual Learning for Text Classification with Information Disentanglement Based Regularization. NAACL-HLT (2021)
Ananth Balashankar, Xuezhi Wang, Ben Packer, Nithum Thain, Ed H. Chi, Alex Beutel
Can We Improve Model Robustness through Secondary Attribute Counterfactuals? EMNLP (1) (2021)
Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi
Improving Uncertainty Estimates through the Relationship with Adversarial Robustness. CoRR (2020)
Alexander D'Amour, Katherine A. Heller, Dan Moldovan, Ben Adlam, Babak Alipanahi, Alex Beutel, Christina Chen, Jonathan Deaton, Jacob Eisenstein, Matthew D. Hoffman, Farhad Hormozdiari, Neil Houlsby, Shaobo Hou, Ghassen Jerfel, Alan Karthikesalingam, Mario Lucic, Yi-An Ma, Cory Y. McLean, Diana Mincu, Akinori Mitani, Andrea Montanari, Zachary Nado, Vivek Natarajan, Christopher Nielson, Thomas F. Osborne, Rajiv Raman, Kim Ramasamy, Rory Sayres, Jessica Schrouff, Martin Seneviratne, Shannon Sequeira, Harini Suresh, Victor Veitch, Max Vladymyrov, Xuezhi Wang, Kellie Webster, Steve Yadlowsky, Taedong Yun, Xiaohua Zhai, D. Sculley
Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR (2020)
Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed Chi
Fairness without Demographics through Adversarially Reweighted Learning. NeurIPS (2020)
Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed Chi
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. CoRR (2020)
Ankur P. Parikh, Xuezhi Wang, Sebastian Gehrmann, Manaal Faruqui, Bhuwan Dhingra, Diyi Yang, Dipanjan Das
ToTTo: A Controlled Table-To-Text Generation Dataset. EMNLP (1) (2020)
Ankur P. Parikh, Xuezhi Wang, Sebastian Gehrmann, Manaal Faruqui, Bhuwan Dhingra, Diyi Yang, Dipanjan Das
ToTTo: A Controlled Table-To-Text Generation Dataset. CoRR (2020)
Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi
Fairness without Demographics through Adversarially Reweighted Learning. CoRR (2020)
Kellie Webster, Xuezhi Wang, Ian Tenney, Alex Beutel, Emily Pitler, Ellie Pavlick, Jilin Chen, Slav Petrov
Measuring and Reducing Gendered Correlations in Pre-trained Models. CoRR (2020)
Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed Chi
CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. EMNLP (1) (2020)
Saehan Jo, Immanuel Trummer, Weicheng Yu, Xuezhi Wang, Cong Yu, Daniel Liu, Niyati Mehta
Verifying Text Summaries of Relational Data Sets. SIGMOD Conference (2019)
Flip Korn, Xuezhi Wang, You Wu, Cong Yu
Automatically Generating Interesting Facts from Wikipedia Tables. SIGMOD Conference (2019)
Silu Huang, Jialu Liu, Flip Korn, Xuezhi Wang, You Wu, Dale Markowitz, Cong Yu
Contextual Fact Ranking and Its Applications in Table Synthesis and Compression. KDD (2019)
Candice Schumann, Xuezhi Wang, Alex Beutel, Jilin Chen, Hai Qian, Ed H. Chi
Transfer of Machine Learning Fairness across Domains. CoRR (2019)
Saehan Jo, Immanuel Trummer, Weicheng Yu, Xuezhi Wang, Cong Yu, Daniel Liu, Niyati Mehta
AggChecker: A Fact-Checking System for Text Summaries of Relational Data Sets. Proc. VLDB Endow. 12 (12) (2019)
Xuezhi Wang, Nithum Thain, Anu Sinha, Ed H. Chi, Jilin Chen, Alex Beutel
Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems. CoRR (2019)
Georgios Karagiannis, Immanuel Trummer, Saehan Jo, Shubham Khandelwal, Xuezhi Wang, Cong Yu
Mining an "Anti-Knowledge Base" from Wikipedia Updates with Applications to Fact Checking and Beyond. Proc. VLDB Endow. 13 (4) (2019)
Xuezhi Wang, Cong Yu
Summarizing News Articles Using Question-and-Answer Pairs via Learning. ISWC (1) (2019)
Xuezhi Wang, Cong Yu, Simon Baumgartner, Flip Korn
Relevant Document Discovery for Fact-Checking Articles. WWW (Companion Volume) (2018)
Xuezhi Wang, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems. IJCAI (2016)
Xuezhi Wang, Jeff G. Schneider
Generalization Bounds for Transfer Learning under Model Shift. UAI (2015)
Xuezhi Wang, Tzu-Kuo Huang, Jeff G. Schneider
Active Transfer Learning under Model Shift. ICML (2014)
Rahul Gupta, Alon Y. Halevy, Xuezhi Wang, Steven Euijong Whang, Fei Wu
Biperpedia: An Ontology for Search Applications. Proc. VLDB Endow. 7 (7) (2014)
Xuezhi Wang, Jeff G. Schneider
Flexible Transfer Learning under Support and Model Shift. NIPS (2014)
Xuezhi Wang, Roman Garnett, Jeff G. Schneider
Active search on graphs. KDD (2013)
Xuezhi Wang, Jie Tang, Hong Cheng, Philip S. Yu
ADANA: Active Name Disambiguation. ICDM (2011)