Xuezhi Wang - RankMe

95 papers A* 23A 2C 1Journal 50Unranked 19

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Comprehensive Metapath-based Heterogeneous Graph Transformer for Gene-Disease Association Prediction. CoRR Wentao Cui, Shoubo Li, Chen Fang, Qingqing Long, Chengrui Wang, Xuezhi Wang, Yuanchun Zhou
2025	J	`jnl`	Ming-UniAudio: Speech LLM for Joint Understanding, Generation and Editing with Unified Representation. CoRR Canxiang Yan, Chunxiang Jin, Dawei Huang, Haibing Yu, Han Peng, Hui Zhan, Jie Gao, Jing Peng, Jingdong Chen, Jun Zhou, Kaimeng Ren, Ming Yang, Mingxue Yang, Qiang Xu, Qin Zhao, Ruijie Xiong, Shaoxiong Lin, Xuezhi Wang, Yi Yuan, Yifei Wu, Yongjie Lyu, Zhengyu He, Zhihao Qiu, Zhiqiang Fang, Ziyuan Huang
2024	J	`jnl`	A Minimalist Prompt for Zero-Shot Policy Learning. CoRR Meng Song, Xuezhi Wang, Tanay Biradar, Yao Qin, Manmohan Chandraker
2024	A*	`conf`	Chain-of-Thought Reasoning Without Prompting. NeurIPS Xuezhi Wang, Denny Zhou
2024	J	`jnl`	Chain-of-Thought Reasoning Without Prompting. CoRR Xuezhi Wang, Denny Zhou
2024	—	`conf`	Comprehensive Metapath-based Heterogeneous Graph Transformer for Gene-Disease Association Prediction. BIBM Wentao Cui, Shoubo Li, Chen Fang, Qingqing Long, Chengrui Wang, Xuezhi Wang, Yuanchun Zhou
2024	—	`conf`	FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation. ACL (Findings) 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
2024	A*	`conf`	Large Language Models as Optimizers. ICLR Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen
2024	A*	`conf`	Large Language Models as Tool Makers. ICLR Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou
2024	A*	`conf`	Premise Order Matters in Reasoning with Large Language Models. ICML Xinyun Chen, Ryan A. Chi, Xuezhi Wang, Denny Zhou
2024	J	`jnl`	Premise Order Matters in Reasoning with Large Language Models. CoRR Xinyun Chen, Ryan A. Chi, Xuezhi Wang, Denny Zhou
2024	J	`jnl`	Scaling Instruction-Finetuned Language Models. J. Mach. Learn. Res. Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, Albert Webson, Shixiang Shane Gu, Zhuyun Dai, Mirac Suzgun, Xinyun Chen, Aakanksha Chowdhery, Alex Castro-Ros, Marie Pellat, Kevin Robinson, Dasha Valter, 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
2024	J	`jnl`	Transformers Can Achieve Length Generalization But Not Robustly. CoRR Yongchao Zhou, Uri Alon, Xinyun Chen, Xuezhi Wang, Rishabh Agarwal, Denny Zhou
2023	A*	`conf`	A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures. CHI Amanda Baughan, Xuezhi Wang, Ariel Liu, Allison Mercurio, Jilin Chen, Xiao Ma
2023	J	`jnl`	A Mixed-Methods Approach to Understanding User Trust after Voice Assistant Failures. CoRR Amanda Baughan, Allison Mercurio, Ariel Liu, Xuezhi Wang, Jilin Chen, Xiao Ma
2023	—	`conf`	Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints. EACL (Findings) Albert Lu, Hongxin Zhang, Yanzhe Zhang, Xuezhi Wang, Diyi Yang
2023	J	`jnl`	Bounding the Capabilities of Large Language Models in Open Text Generation with Prompt Constraints. CoRR Albert Lu, Hongxin Zhang, Yanzhe Zhang, Xuezhi Wang, Diyi Yang
2023	J	`jnl`	FreshLLMs: Refreshing Large Language Models with Search Engine Augmentation. CoRR 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
2023	A*	`conf`	Grammar Prompting for Domain-Specific Language Generation with Large Language Models. NeurIPS Bailin Wang, Zi Wang, Xuezhi Wang, Yuan Cao, Rif A. Saurous, Yoon Kim
2023	J	`jnl`	Grammar Prompting for Domain-Specific Language Generation with Large Language Models. CoRR Bailin Wang, Zi Wang, Xuezhi Wang, Yuan Cao, Rif A. Saurous, Yoon Kim
2023	J	`jnl`	Improving Classifier Robustness through Active Generation of Pairwise Counterfactuals. CoRR Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Jilin Chen, Ed H. Chi, Alex Beutel
2023	—	`conf`	Improving Classifier Robustness through Active Generative Counterfactual Data Augmentation. EMNLP (Findings) Ananth Balashankar, Xuezhi Wang, Yao Qin, Ben Packer, Nithum Thain, Ed H. Chi, Jilin Chen, Alex Beutel
2023	A*	`conf`	Language models are multilingual chain-of-thought reasoners. ICLR 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
2023	A*	`conf`	Large Language Models Can Self-Improve. EMNLP Jiaxin Huang, Shixiang Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han
2023	J	`jnl`	Large Language Models as Optimizers. CoRR Chengrun Yang, Xuezhi Wang, Yifeng Lu, Hanxiao Liu, Quoc V. Le, Denny Zhou, Xinyun Chen
2023	J	`jnl`	Large Language Models as Tool Makers. CoRR Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, Denny Zhou
2023	A*	`conf`	Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. ICLR Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Claire Cui, Olivier Bousquet, Quoc V. Le, Ed H. Chi
2023	J	`jnl`	PaLM: Scaling Language Modeling with Pathways. J. Mach. Learn. Res. 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
2023	A*	`conf`	Recitation-Augmented Language Models. ICLR Zhiqing Sun, Xuezhi Wang, Yi Tay, Yiming Yang, Denny Zhou
2023	A*	`conf`	Self-Consistency Improves Chain of Thought Reasoning in Language Models. ICLR Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou
2023	A*	`conf`	TEMPERA: Test-Time Prompt Editing via Reinforcement Learning. ICLR Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez
2023	J	`jnl`	Towards Robust Prompts on Vision-Language Models. CoRR Jindong Gu, Ahmad Beirami, Xuezhi Wang, Alex Beutel, Philip H. S. Torr, Yao Qin
2023	A*	`conf`	UL2: Unifying Language Learning Paradigms. ICLR 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
2023	J	`jnl`	Universal Self-Consistency for Large Language Model Generation. CoRR Xinyun Chen, Renat Aksitov, Uri Alon, Jie Ren, Kefan Xiao, Pengcheng Yin, Sushant Prakash, Charles Sutton, Xuezhi Wang, Denny Zhou
2023	—	`conf`	What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. SaTML Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel
2023	J	`jnl`	What Are Effective Labels for Augmented Data? Improving Calibration and Robustness with AutoLabel. CoRR Yao Qin, Xuezhi Wang, Balaji Lakshminarayanan, Ed H. Chi, Alex Beutel
2022	J	`jnl`	Chain of Thought Prompting Elicits Reasoning in Large Language Models. CoRR Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Ed H. Chi, Quoc Le, Denny Zhou
2022	A*	`conf`	Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. NeurIPS Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, Denny Zhou
2022	—	`conf`	Continual Sequence Generation with Adaptive Compositional Modules. ACL (1) Yanzhe Zhang, Xuezhi Wang, Diyi Yang
2022	J	`jnl`	Continual Sequence Generation with Adaptive Compositional Modules. CoRR Yanzhe Zhang, Xuezhi Wang, Diyi Yang
2022	—	`conf`	Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models. NAACL-HLT (Findings) Tianlu Wang, Rohit Sridhar, Diyi Yang, Xuezhi Wang
2022	—	`conf`	Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers. EMNLP (Findings) Jieyu Zhao, Xuezhi Wang, Yao Qin, Jilin Chen, Kai-Wei Chang
2022	J	`jnl`	Investigating Ensemble Methods for Model Robustness Improvement of Text Classifiers. CoRR Jieyu Zhao, Xuezhi Wang, Yao Qin, Jilin Chen, Kai-Wei Chang
2022	J	`jnl`	Language Models are Multilingual Chain-of-Thought Reasoners. CoRR 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
2022	J	`jnl`	Large Language Models Can Self-Improve. CoRR Jiaxin Huang, Shixiang Shane Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, Jiawei Han
2022	J	`jnl`	Least-to-Most Prompting Enables Complex Reasoning in Large Language Models. CoRR Denny Zhou, Nathanael Schärli, Le Hou, Jason Wei, Nathan Scales, Xuezhi Wang, Dale Schuurmans, Olivier Bousquet, Quoc Le, Ed H. Chi
2022	—	`conf`	Measure and Improve Robustness in NLP Models: A Survey. NAACL-HLT Xuezhi Wang, Haohan Wang, Diyi Yang
2022	J	`jnl`	PaLM: Scaling Language Modeling with Pathways. CoRR 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
2022	J	`jnl`	Rationale-Augmented Ensembles in Language Models. CoRR Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou
2022	J	`jnl`	Recitation-Augmented Language Models. CoRR Zhiqing Sun, Xuezhi Wang, Yi Tay, Yiming Yang, Denny Zhou
2022	J	`jnl`	Scaling Instruction-Finetuned Language Models. CoRR 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
2022	J	`jnl`	Self-Consistency Improves Chain of Thought Reasoning in Language Models. CoRR Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V. Le, Ed H. Chi, Denny Zhou
2022	J	`jnl`	TEMPERA: Test-Time Prompting via Reinforcement Learning. CoRR Tianjun Zhang, Xuezhi Wang, Denny Zhou, Dale Schuurmans, Joseph E. Gonzalez
2022	J	`jnl`	Underspecification Presents Challenges for Credibility in Modern Machine Learning. J. Mach. Learn. Res. 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
2022	A*	`conf`	Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. NeurIPS Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang
2021	—	`conf`	Can We Improve Model Robustness through Secondary Attribute Counterfactuals? EMNLP (1) Ananth Balashankar, Xuezhi Wang, Ben Packer, Nithum Thain, Ed H. Chi, Alex Beutel
2021	—	`conf`	Continual Learning for Text Classification with Information Disentanglement Based Regularization. NAACL-HLT Yufan Huang, Yanzhe Zhang, Jiaao Chen, Xuezhi Wang, Diyi Yang
2021	J	`jnl`	Continual Learning for Text Classification with Information Disentanglement Based Regularization. CoRR Yufan Huang, Yanzhe Zhang, Jiaao Chen, Xuezhi Wang, Diyi Yang
2021	—	`conf`	Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information. FAccT Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang
2021	J	`jnl`	Evaluating Fairness of Machine Learning Models Under Uncertain and Incomplete Information. CoRR Pranjal Awasthi, Alex Beutel, Matthäus Kleindessner, Jamie Morgenstern, Xuezhi Wang
2021	J	`jnl`	Identifying and Mitigating Spurious Correlations for Improving Robustness in NLP Models. CoRR Tianlu Wang, Diyi Yang, Xuezhi Wang
2021	A*	`conf`	Improving Calibration through the Relationship with Adversarial Robustness. NeurIPS Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi
2021	J	`jnl`	Measure and Improve Robustness in NLP Models: A Survey. CoRR Xuezhi Wang, Haohan Wang, Diyi Yang
2021	C	`conf`	Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. AIES Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
2021	J	`jnl`	Measuring Model Fairness under Noisy Covariates: A Theoretical Perspective. CoRR Flavien Prost, Pranjal Awasthi, Nick Blumm, Aditee Kumthekar, Trevor Potter, Li Wei, Xuezhi Wang, Ed H. Chi, Jilin Chen, Alex Beutel
2021	J	`jnl`	Measuring Recommender System Effects with Simulated Users. CoRR Sirui Yao, Yoni Halpern, Nithum Thain, Xuezhi Wang, Kang Lee, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
2021	A	`conf`	Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems. WSDM Xuezhi Wang, Nithum Thain, Anu Sinha, Flavien Prost, Ed H. Chi, Jilin Chen, Alex Beutel
2021	A*	`conf`	Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. KDD Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
2021	J	`jnl`	Understanding and Improving Fairness-Accuracy Trade-offs in Multi-Task Learning. CoRR Yuyan Wang, Xuezhi Wang, Alex Beutel, Flavien Prost, Jilin Chen, Ed H. Chi
2021	J	`jnl`	Understanding and Improving Robustness of Vision Transformers through Patch-based Negative Augmentation. CoRR Yao Qin, Chiyuan Zhang, Ting Chen, Balaji Lakshminarayanan, Alex Beutel, Xuezhi Wang
2020	—	`conf`	CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. EMNLP (1) Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi
2020	J	`jnl`	CAT-Gen: Improving Robustness in NLP Models via Controlled Adversarial Text Generation. CoRR Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, Ed H. Chi
2020	A*	`conf`	Fairness without Demographics through Adversarially Reweighted Learning. NeurIPS Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi
2020	J	`jnl`	Fairness without Demographics through Adversarially Reweighted Learning. CoRR Preethi Lahoti, Alex Beutel, Jilin Chen, Kang Lee, Flavien Prost, Nithum Thain, Xuezhi Wang, Ed H. Chi
2020	J	`jnl`	Improving Uncertainty Estimates through the Relationship with Adversarial Robustness. CoRR Yao Qin, Xuezhi Wang, Alex Beutel, Ed H. Chi
2020	J	`jnl`	Measuring and Reducing Gendered Correlations in Pre-trained Models. CoRR Kellie Webster, Xuezhi Wang, Ian Tenney, Alex Beutel, Emily Pitler, Ellie Pavlick, Jilin Chen, Slav Petrov
2020	—	`conf`	ToTTo: A Controlled Table-To-Text Generation Dataset. EMNLP (1) Ankur P. Parikh, Xuezhi Wang, Sebastian Gehrmann, Manaal Faruqui, Bhuwan Dhingra, Diyi Yang, Dipanjan Das
2020	J	`jnl`	ToTTo: A Controlled Table-To-Text Generation Dataset. CoRR Ankur P. Parikh, Xuezhi Wang, Sebastian Gehrmann, Manaal Faruqui, Bhuwan Dhingra, Diyi Yang, Dipanjan Das
2020	J	`jnl`	Underspecification Presents Challenges for Credibility in Modern Machine Learning. CoRR 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
2019	J	`jnl`	AggChecker: A Fact-Checking System for Text Summaries of Relational Data Sets. Proc. VLDB Endow. Saehan Jo, Immanuel Trummer, Weicheng Yu, Xuezhi Wang, Cong Yu, Daniel Liu, Niyati Mehta
2019	—	`conf`	Automatically Generating Interesting Facts from Wikipedia Tables. SIGMOD Conference Flip Korn, Xuezhi Wang, You Wu, Cong Yu
2019	A*	`conf`	Contextual Fact Ranking and Its Applications in Table Synthesis and Compression. KDD Silu Huang, Jialu Liu, Flip Korn, Xuezhi Wang, You Wu, Dale Markowitz, Cong Yu
2019	J	`jnl`	Mining an "Anti-Knowledge Base" from Wikipedia Updates with Applications to Fact Checking and Beyond. Proc. VLDB Endow. Georgios Karagiannis, Immanuel Trummer, Saehan Jo, Shubham Khandelwal, Xuezhi Wang, Cong Yu
2019	J	`jnl`	Practical Compositional Fairness: Understanding Fairness in Multi-Task ML Systems. CoRR Xuezhi Wang, Nithum Thain, Anu Sinha, Ed H. Chi, Jilin Chen, Alex Beutel
2019	—	`conf`	Summarizing News Articles Using Question-and-Answer Pairs via Learning. ISWC (1) Xuezhi Wang, Cong Yu
2019	J	`jnl`	Transfer of Machine Learning Fairness across Domains. CoRR Candice Schumann, Xuezhi Wang, Alex Beutel, Jilin Chen, Hai Qian, Ed H. Chi
2019	—	`conf`	Verifying Text Summaries of Relational Data Sets. SIGMOD Conference Saehan Jo, Immanuel Trummer, Weicheng Yu, Xuezhi Wang, Cong Yu, Daniel Liu, Niyati Mehta
2018	—	`conf`	Relevant Document Discovery for Fact-Checking Articles. WWW (Companion Volume) Xuezhi Wang, Cong Yu, Simon Baumgartner, Flip Korn
2016	A*	`conf`	Nonparametric Risk and Stability Analysis for Multi-Task Learning Problems. IJCAI Xuezhi Wang, Junier B. Oliva, Jeff G. Schneider, Barnabás Póczos
2015	A	`conf`	Generalization Bounds for Transfer Learning under Model Shift. UAI Xuezhi Wang, Jeff G. Schneider
2014	A*	`conf`	Active Transfer Learning under Model Shift. ICML Xuezhi Wang, Tzu-Kuo Huang, Jeff G. Schneider
2014	J	`jnl`	Biperpedia: An Ontology for Search Applications. Proc. VLDB Endow. Rahul Gupta, Alon Y. Halevy, Xuezhi Wang, Steven Euijong Whang, Fei Wu
2014	—	`conf`	Flexible Transfer Learning under Support and Model Shift. NIPS Xuezhi Wang, Jeff G. Schneider
2013	A*	`conf`	Active search on graphs. KDD Xuezhi Wang, Roman Garnett, Jeff G. Schneider
2011	A*	`conf`	ADANA: Active Name Disambiguation. ICDM Xuezhi Wang, Jie Tang, Hong Cheng, Philip S. Yu