Ruiqi Zhong

According to our database, Ruiqi Zhong authored at least 29 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Language Models Learn to Mislead Humans via RLHF.

Jiaxin Wen, Ruiqi Zhong, Akbir Khan, Ethan Perez, Jacob Steinhardt, Minlie Huang, Samuel R. Bowman, He He, Shi Feng

CoRR, 2024

Explaining Datasets in Words: Statistical Models with Natural Language Parameters.

Ruiqi Zhong, Heng Wang, Dan Klein, Jacob Steinhardt

CoRR, 2024

Foundational Challenges in Assuring Alignment and Safety of Large Language Models.

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

CoRR, 2024

Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations.

Yanda Chen, Ruiqi Zhong, Narutatsu Ri, Chen Zhao, He He, Jacob Steinhardt, Zhou Yu, Kathleen R. McKeown

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Describing Differences in Image Sets with Natural Language.

Lisa Dunlap, Yuhui Zhang, Xiaohan Wang, Ruiqi Zhong, Trevor Darrell, Jacob Steinhardt, Joseph E. Gonzalez, Serena Yeung-Levy

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

Learning Task Decomposition to Assist Humans in Competitive Programming.

Jiaxin Wen, Ruiqi Zhong, Pei Ke, Zhihong Shao, Hongning Wang, Minlie Huang

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Goal Driven Discovery of Distributional Differences via Language Descriptions.

Ruiqi Zhong, Peter Zhang, Steve Li, Jinwoo Ahn, Dan Klein, Jacob Steinhardt

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation.

Yuhang Lai, Chengxi Li, Yiming Wang, Tianyi Zhang, Ruiqi Zhong, Luke Zettlemoyer, Wen-Tau Yih, Daniel Fried, Sida I. Wang, Tao Yu

Proceedings of the International Conference on Machine Learning, 2023

InCoder: A Generative Model for Code Infilling and Synthesis.

Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Scott Yih, Luke Zettlemoyer, Mike Lewis

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL.

Ruiqi Zhong, Charlie Snell, Dan Klein, Jason Eisner

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Goal-Driven Explainable Clustering via Language Descriptions.

Zihan Wang, Jingbo Shang, Ruiqi Zhong

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

2022

Learning by Distilling Context.

Charlie Snell, Dan Klein, Ruiqi Zhong

CoRR, 2022

Active Programming by Example with a Natural Language Prior.

Ruiqi Zhong, Charlie Snell, Dan Klein, Jason Eisner

CoRR, 2022

Summarizing Differences between Text Distributions with Natural Language.

Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt

CoRR, 2022

Describing Differences between Text Distributions with Natural Language.

Ruiqi Zhong, Charlie Snell, Dan Klein, Jacob Steinhardt

Proceedings of the International Conference on Machine Learning, 2022

UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models.

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

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Meta-learning via Language Model In-context Tuning.

Yanda Chen, Ruiqi Zhong, Sheng Zha, George Karypis, He He

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

2021

The Effect of Model Size on Worst-Group Generalization.

Alan Pham, Eunice Chan, Vikranth Srivatsa, Dhruba Ghosh, Yaoqing Yang, Yaodong Yu, Ruiqi Zhong, Joseph E. Gonzalez, Jacob Steinhardt

CoRR, 2021

Meta-tuning Language Models to Answer Prompts Better.

Ruiqi Zhong, Kristy Lee, Zheng Zhang, Dan Klein

CoRR, 2021

Approximating How Single Head Attention Learns.

Charlie Snell, Ruiqi Zhong, Dan Klein, Jacob Steinhardt

CoRR, 2021

Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections.

Ruiqi Zhong, Kristy Lee, Zheng Zhang, Dan Klein

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level.

Ruiqi Zhong, Dhruba Ghosh, Dan Klein, Jacob Steinhardt

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

Semantic Evaluation for Text-to-SQL with Distilled Test Suites.

Ruiqi Zhong, Tao Yu, Dan Klein

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Semantic Scaffolds for Pseudocode-to-Code Generation.

Ruiqi Zhong, Mitchell Stern, Dan Klein

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Fine-grained Sentiment Analysis with Faithful Attention.

Ruiqi Zhong, Steven Shao, Kathleen R. McKeown

CoRR, 2019

Detecting and Reducing Bias in a High Stakes Domain.

Ruiqi Zhong, Yanda Chen, Desmond Patton, Charlotte Selous, Kathy McKeown

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

GAIA - A Multi-media Multi-lingual Knowledge Extraction and Hypothesis Generation System.

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

Proceedings of the 2018 Text Analysis Conference, 2018

Subspace Embedding and Linear Regression with Orlicz Norm.

Alexandr Andoni, Chengyu Lin, Ying Sheng, Peilin Zhong, Ruiqi Zhong

Proceedings of the 35th International Conference on Machine Learning, 2018

Detecting Gang-Involved Escalation on Social Media Using Context.

Serina Chang, Ruiqi Zhong, Ethan Adams, Fei-Tzin Lee, Siddharth Varia, Desmond Patton, William R. Frey, Chris Kedzie, Kathy McKeown

Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018