Ruiqi Zhong

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 40

Top Topics

Linear Regression

Structured Knowledge

Top Venues

Publications

Jiaxin Wen, Ruiqi Zhong, Pei Ke, Zhihong Shao, Hongning Wang, Minlie Huang
Learning Task Decomposition to Assist Humans in Competitive Programming. ACL (1) (2024)
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 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
Foundational Challenges in Assuring Alignment and Safety of Large Language Models. CoRR (2024)
Jiaxin Wen, Ruiqi Zhong, Pei Ke, Zhihong Shao, Hongning Wang, Minlie Huang
Learning Task Decomposition to Assist Humans in Competitive Programming. CoRR (2024)
Lisa Dunlap, Yuhui Zhang, Xiaohan Wang, Ruiqi Zhong, Trevor Darrell, Jacob Steinhardt, Joseph E. Gonzalez, Serena Yeung-Levy
Describing Differences in Image Sets with Natural Language. CoRR (2023)
Ruiqi Zhong, Peter Zhang, Steve Li, Jinwoo Ahn, Dan Klein, Jacob Steinhardt
Goal Driven Discovery of Distributional Differences via Language Descriptions. NeurIPS (2023)
Yuhang Lai, Chengxi Li, Yiming Wang, Tianyi Zhang, Ruiqi Zhong, Luke Zettlemoyer, Wen-Tau Yih, Daniel Fried, Sida I. Wang, Tao Yu
DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation. ICML (2023)
Zihan Wang, Jingbo Shang, Ruiqi Zhong
Goal-Driven Explainable Clustering via Language Descriptions. EMNLP (2023)
Ruiqi Zhong, Peter Zhang, Steve Li, Jinwoo Ahn, Dan Klein, Jacob Steinhardt
Goal Driven Discovery of Distributional Differences via Language Descriptions. CoRR (2023)
Ruiqi Zhong, Charlie Snell, Dan Klein, Jason Eisner
Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL. EMNLP (2023)
Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Scott Yih, Luke Zettlemoyer, Mike Lewis
InCoder: A Generative Model for Code Infilling and Synthesis. ICLR (2023)
Zihan Wang, Jingbo Shang, Ruiqi Zhong
Goal-Driven Explainable Clustering via Language Descriptions. CoRR (2023)
Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He, Jacob Steinhardt, Zhou Yu, Kathleen R. McKeown
Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations. CoRR (2023)
Charlie Snell, Dan Klein, Ruiqi Zhong
Learning by Distilling Context. CoRR (2022)
Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt
Describing Differences between Text Distributions with Natural Language. ICML (2022)
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
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. EMNLP (2022)
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
Meta-learning via Language Model In-context Tuning. ACL (1) (2022)
Yuhang Lai, Chengxi Li, Yiming Wang, Tianyi Zhang, Ruiqi Zhong, Luke Zettlemoyer, Scott Wen-tau Yih, Daniel Fried, Sida I. Wang, Tao Yu
DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation. CoRR (2022)
Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, Mike Lewis
InCoder: A Generative Model for Code Infilling and Synthesis. CoRR (2022)
Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt
Summarizing Differences between Text Distributions with Natural Language. CoRR (2022)
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
UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models. CoRR (2022)
Ruiqi Zhong, Charlie Snell, Dan Klein, Jason Eisner
Active Programming by Example with a Natural Language Prior. CoRR (2022)
Ruiqi Zhong, Kristy Lee, Zheng Zhang, Dan Klein
Meta-tuning Language Models to Answer Prompts Better. CoRR (2021)
Ruiqi Zhong, Dhruba Ghosh, Dan Klein, Jacob Steinhardt
Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level. ACL/IJCNLP (Findings) (2021)
Ruiqi Zhong, Dhruba Ghosh, Dan Klein, Jacob Steinhardt
Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level. CoRR (2021)
Alan Pham, Eunice Chan, Vikranth Srivatsa, Dhruba Ghosh, Yaoqing Yang, Yaodong Yu, Ruiqi Zhong, Joseph E. Gonzalez, Jacob Steinhardt
The Effect of Model Size on Worst-Group Generalization. CoRR (2021)
Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He
Meta-learning via Language Model In-context Tuning. CoRR (2021)
Ruiqi Zhong, Kristy Lee, Zheng Zhang, Dan Klein
Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections. EMNLP (Findings) (2021)
Charlie Snell, Ruiqi Zhong, Dan Klein, Jacob Steinhardt
Approximating How Single Head Attention Learns. CoRR (2021)
Ruiqi Zhong, Tao Yu, Dan Klein
Semantic Evaluation for Text-to-SQL with Distilled Test Suites. EMNLP (1) (2020)
Ruiqi Zhong, Mitchell Stern, Dan Klein
Semantic Scaffolds for Pseudocode-to-Code Generation. ACL (2020)
Ruiqi Zhong, Mitchell Stern, Dan Klein
Semantic Scaffolds for Pseudocode-to-Code Generation. CoRR (2020)
Ruiqi Zhong, Tao Yu, Dan Klein
Semantic Evaluation for Text-to-SQL with Distilled Test Suites. CoRR (2020)
Ruiqi Zhong, Yanda Chen, Desmond Patton, Charlotte Selous, Kathy McKeown
Detecting and Reducing Bias in a High Stakes Domain. CoRR (2019)
Ruiqi Zhong, Steven Shao, Kathleen R. McKeown
Fine-grained Sentiment Analysis with Faithful Attention. CoRR (2019)
Ruiqi Zhong, Yanda Chen, Desmond Patton, Charlotte Selous, Kathy McKeown
Detecting and Reducing Bias in a High Stakes Domain. EMNLP/IJCNLP (1) (2019)
Serina Chang, Ruiqi Zhong, Ethan Adams, Fei-Tzin Lee, Siddharth Varia, Desmond Patton, William R. Frey, Chris Kedzie, Kathy McKeown
Detecting Gang-Involved Escalation on Social Media Using Context. CoRR (2018)
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
GAIA - A Multi-media Multi-lingual Knowledge Extraction and Hypothesis Generation System. TAC (2018)
Alexandr Andoni, Chengyu Lin, Ying Sheng, Peilin Zhong, Ruiqi Zhong
Subspace Embedding and Linear Regression with Orlicz Norm. ICML (2018)
Serina Chang, Ruiqi Zhong, Ethan Adams, Fei-Tzin Lee, Siddharth Varia, Desmond Patton, William R. Frey, Chris Kedzie, Kathy McKeown
Detecting Gang-Involved Escalation on Social Media Using Context. EMNLP (2018)
Alexandr Andoni, Chengyu Lin, Ying Sheng, Peilin Zhong, Ruiqi Zhong
Subspace Embedding and Linear Regression with Orlicz Norm. CoRR (2018)