Ruiqi Zhong - RankMe

49 papers A* 14Journal 27Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming. CoRR Mrinank Sharma, Meg Tong, Jesse Mu, Jerry Wei, Jorrit Kruthoff, Scott Goodfriend, Euan Ong, Alwin Peng, Raj Agarwal, Cem Anil, Amanda Askell, Nathan Bailey, Joe Benton, Emma Bluemke, Samuel R. Bowman, Eric Christiansen, Hoagy Cunningham, Andy Dau, Anjali Gopal, Rob Gilson, Logan Graham, Logan Howard, Nimit Kalra, Taesung Lee, Kevin Lin, Peter Lofgren, Francesco Mosconi, Clare O'Hara, Catherine Olsson, Linda Petrini, Samir Rajani, Nikhil Saxena, Alex Silverstein, Tanya Singh, Theodore R. Sumers, Leonard Tang, Kevin K. Troy, Constantin Weisser, Ruiqi Zhong, Giulio Zhou, Jan Leike, Jared Kaplan, Ethan Perez
2025	A*	`conf`	Language Models Learn to Mislead Humans via RLHF. ICLR Jiaxin Wen, Ruiqi Zhong, Akbir Khan, Ethan Perez, Jacob Steinhardt, Minlie Huang, Samuel R. Bowman, He He, Shi Feng
2025	—	`conf`	Language Models can Categorize System Inputs for Performance Analysis. NAACL (Long Papers) Dominic Sobhani, Ruiqi Zhong, Edison Marrese-Taylor, Keisuke Sakaguchi, Yutaka Matsuo
2024	A*	`conf`	Describing Differences in Image Sets with Natural Language. CVPR Lisa Dunlap, Yuhui Zhang, Xiaohan Wang, Ruiqi Zhong, Trevor Darrell, Jacob Steinhardt, Joseph E. Gonzalez, Serena Yeung-Levy
2024	A*	`conf`	Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations. ICML Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He, Jacob Steinhardt, Zhou Yu, Kathleen R. McKeown
2024	A*	`conf`	Explaining Datasets in Words: Statistical Models with Natural Language Parameters. NeurIPS Ruiqi Zhong, Heng Wang, Dan Klein, Jacob Steinhardt
2024	J	`jnl`	Explaining Datasets in Words: Statistical Models with Natural Language Parameters. CoRR Ruiqi Zhong, Heng Wang, Dan Klein, Jacob Steinhardt
2024	J	`jnl`	Foundational Challenges in Assuring Alignment and Safety of Large Language Models. CoRR Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi C. Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Yoshua Bengio, Danqi Chen, Samuel Albanie, Tegan Maharaj, Jakob N. Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger
2024	J	`jnl`	Foundational Challenges in Assuring Alignment and Safety of Large Language Models. Trans. Mach. Learn. Res. Usman Anwar, Abulhair Saparov, Javier Rando, Daniel Paleka, Miles Turpin, Peter Hase, Ekdeep Singh Lubana, Erik Jenner, Stephen Casper, Oliver Sourbut, Benjamin L. Edelman, Zhaowei Zhang, Mario Günther, Anton Korinek, José Hernández-Orallo, Lewis Hammond, Eric J. Bigelow, Alexander Pan, Lauro Langosco, Tomasz Korbak, Heidi Chenyu Zhang, Ruiqi Zhong, Seán Ó hÉigeartaigh, Gabriel Recchia, Giulio Corsi, Alan Chan, Markus Anderljung, Lilian Edwards, Aleksandar Petrov, Christian Schröder de Witt, Sumeet Ramesh Motwani, Yoshua Bengio, Danqi Chen, Philip Torr, Samuel Albanie, Tegan Maharaj, Jakob Nicolaus Foerster, Florian Tramèr, He He, Atoosa Kasirzadeh, Yejin Choi, David Krueger
2024	J	`jnl`	Language Models Learn to Mislead Humans via RLHF. CoRR Jiaxin Wen, Ruiqi Zhong, Akbir Khan, Ethan Perez, Jacob Steinhardt, Minlie Huang, Samuel R. Bowman, He He, Shi Feng
2024	—	`conf`	Learning Task Decomposition to Assist Humans in Competitive Programming. ACL (1) Jiaxin Wen, Ruiqi Zhong, Pei Ke, Zhihong Shao, Hongning Wang, Minlie Huang
2024	J	`jnl`	Learning Task Decomposition to Assist Humans in Competitive Programming. CoRR Jiaxin Wen, Ruiqi Zhong, Pei Ke, Zhihong Shao, Hongning Wang, Minlie Huang
2023	A*	`conf`	DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation. ICML Yuhang Lai, Chengxi Li, Yiming Wang, Tianyi Zhang, Ruiqi Zhong, Luke Zettlemoyer, Wen-tau Yih, Daniel Fried, Sida I. Wang, Tao Yu
2023	J	`jnl`	Describing Differences in Image Sets with Natural Language. CoRR Lisa Dunlap, Yuhui Zhang, Xiaohan Wang, Ruiqi Zhong, Trevor Darrell, Jacob Steinhardt, Joseph E. Gonzalez, Serena Yeung-Levy
2023	J	`jnl`	Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations. CoRR Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He, Jacob Steinhardt, Zhou Yu, Kathleen R. McKeown
2023	A*	`conf`	Goal Driven Discovery of Distributional Differences via Language Descriptions. NeurIPS Ruiqi Zhong, Peter Zhang, Steve Li, Jinwoo Ahn, Dan Klein, Jacob Steinhardt
2023	J	`jnl`	Goal Driven Discovery of Distributional Differences via Language Descriptions. CoRR Ruiqi Zhong, Peter Zhang, Steve Li, Jinwoo Ahn, Dan Klein, Jacob Steinhardt
2023	A*	`conf`	Goal-Driven Explainable Clustering via Language Descriptions. EMNLP Zihan Wang, Jingbo Shang, Ruiqi Zhong
2023	J	`jnl`	Goal-Driven Explainable Clustering via Language Descriptions. CoRR Zihan Wang, Jingbo Shang, Ruiqi Zhong
2023	A*	`conf`	InCoder: A Generative Model for Code Infilling and Synthesis. ICLR Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Scott Yih, Luke Zettlemoyer, Mike Lewis
2023	A*	`conf`	Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL. EMNLP Ruiqi Zhong, Charlie Snell, Dan Klein, Jason Eisner
2022	J	`jnl`	Active Programming by Example with a Natural Language Prior. CoRR Ruiqi Zhong, Charlie Snell, Dan Klein, Jason Eisner
2022	J	`jnl`	DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation. CoRR Yuhang Lai, Chengxi Li, Yiming Wang, Tianyi Zhang, Ruiqi Zhong, Luke Zettlemoyer, Scott Wen-tau Yih, Daniel Fried, Sida I. Wang, Tao Yu
2022	A*	`conf`	Describing Differences between Text Distributions with Natural Language. ICML Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt
2022	J	`jnl`	InCoder: A Generative Model for Code Infilling and Synthesis. CoRR Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, Mike Lewis
2022	J	`jnl`	Learning by Distilling Context. CoRR Charlie Snell, Dan Klein, Ruiqi Zhong
2022	—	`conf`	Meta-learning via Language Model In-context Tuning. ACL (1) Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
2022	J	`jnl`	Summarizing Differences between Text Distributions with Natural Language. CoRR Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt
2022	A*	`conf`	UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. EMNLP Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, Tao Yu
2022	J	`jnl`	UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. CoRR Tianbao Xie, Chen Henry Wu, Peng Shi, Ruiqi Zhong, Torsten Scholak, Michihiro Yasunaga, Chien-Sheng Wu, Ming Zhong, Pengcheng Yin, Sida I. Wang, Victor Zhong, Bailin Wang, Chengzu Li, Connor Boyle, Ansong Ni, Ziyu Yao, Dragomir R. Radev, Caiming Xiong, Lingpeng Kong, Rui Zhang, Noah A. Smith, Luke Zettlemoyer, Tao Yu
2021	—	`conf`	Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections. EMNLP (Findings) Ruiqi Zhong, Kristy Lee, Zheng Zhang, Dan Klein
2021	J	`jnl`	Approximating How Single Head Attention Learns. CoRR Charlie Snell, Ruiqi Zhong, Dan Klein, Jacob Steinhardt
2021	—	`conf`	Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level. ACL/IJCNLP (Findings) Ruiqi Zhong, Dhruba Ghosh, Dan Klein, Jacob Steinhardt
2021	J	`jnl`	Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level. CoRR Ruiqi Zhong, Dhruba Ghosh, Dan Klein, Jacob Steinhardt
2021	J	`jnl`	Meta-learning via Language Model In-context Tuning. CoRR Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
2021	J	`jnl`	Meta-tuning Language Models to Answer Prompts Better. CoRR Ruiqi Zhong, Kristy Lee, Zheng Zhang, Dan Klein
2021	J	`jnl`	The Effect of Model Size on Worst-Group Generalization. CoRR Alan Pham, Eunice Chan, Vikranth Srivatsa, Dhruba Ghosh, Yaoqing Yang, Yaodong Yu, Ruiqi Zhong, Joseph E. Gonzalez, Jacob Steinhardt
2020	—	`conf`	Semantic Evaluation for Text-to-SQL with Distilled Test Suites. EMNLP (1) Ruiqi Zhong, Tao Yu, Dan Klein
2020	J	`jnl`	Semantic Evaluation for Text-to-SQL with Distilled Test Suites. CoRR Ruiqi Zhong, Tao Yu, Dan Klein
2020	A*	`conf`	Semantic Scaffolds for Pseudocode-to-Code Generation. ACL Ruiqi Zhong, Mitchell Stern, Dan Klein
2020	J	`jnl`	Semantic Scaffolds for Pseudocode-to-Code Generation. CoRR Ruiqi Zhong, Mitchell Stern, Dan Klein
2019	—	`conf`	Detecting and Reducing Bias in a High Stakes Domain. EMNLP/IJCNLP (1) Ruiqi Zhong, Yanda Chen, Desmond Patton, Charlotte Selous, Kathy McKeown
2019	J	`jnl`	Detecting and Reducing Bias in a High Stakes Domain. CoRR Ruiqi Zhong, Yanda Chen, Desmond Patton, Charlotte Selous, Kathy McKeown
2019	J	`jnl`	Fine-grained Sentiment Analysis with Faithful Attention. CoRR Ruiqi Zhong, Steven Shao, Kathleen R. McKeown
2018	A*	`conf`	Detecting Gang-Involved Escalation on Social Media Using Context. EMNLP Serina Chang, Ruiqi Zhong, Ethan Adams, Fei-Tzin Lee, Siddharth Varia, Desmond Patton, William R. Frey, Chris Kedzie, Kathy McKeown
2018	J	`jnl`	Detecting Gang-Involved Escalation on Social Media Using Context. CoRR Serina Chang, Ruiqi Zhong, Ethan Adams, Fei-Tzin Lee, Siddharth Varia, Desmond Patton, William R. Frey, Chris Kedzie, Kathy McKeown
2018	—	`conf`	GAIA - A Multi-media Multi-lingual Knowledge Extraction and Hypothesis Generation System. TAC Tongtao Zhang, Ananya Subburathinam, Ge Shi, Lifu Huang, Di Lu, Xiaoman Pan, Manling Li, Boliang Zhang, Qingyun Wang, Spencer Whitehead, Heng Ji, Alireza Zareian, Hassan Akbari, Brian Chen, Ruiqi Zhong, Steven Shao, Emily Allaway, Shih-Fu Chang, Kathleen R. McKeown, Dongyu Li, Xin Huang, Kexuan Sun, Xujun Peng, Ryan Gabbard, Marjorie Freedman, Mayank Kejriwal, Ram Nevatia, Pedro A. Szekely, T. K. Satish Kumar, Ali Sadeghian, Giacomo Bergami, Sourav Dutta, Miguel E. Rodríguez, Daisy Zhe Wang
2018	A*	`conf`	Subspace Embedding and Linear Regression with Orlicz Norm. ICML Alexandr Andoni, Chengyu Lin, Ying Sheng, Peilin Zhong, Ruiqi Zhong
2018	J	`jnl`	Subspace Embedding and Linear Regression with Orlicz Norm. CoRR Alexandr Andoni, Chengyu Lin, Ying Sheng, Peilin Zhong, Ruiqi Zhong