My research focuses on scalable oversight: supervising AI systems to do stuff where the ground truth is expensive to verify.
Doing so requires human-AI collaborations, a better epistemic foundation, and new algorithmic tools.
I currently work on concrete related problems in Natural Language Processing, Machine Learning, and Programming Language, such as
I also have a pretty broad intellectual interest beyond computer
science, such as developmental economy, epistemology, etc.
For example, I am working on a side research project of
measuring social media polarization.
If you are generally interested in Natural Language
Processing and AI, feel free to send me an email and I would
love to chat!
- Enable non-experts to write complex programs.
- Empirically understand how and what neural network learns.
- Build AIs to expand knowledge and inform human decisions.
Describing Differences between Text Distributions with Natural Language
Approximating How Single Head Attention
Charlie Snell, Ruiqi Zhong, Dan Klein, Jacob
[paper] [slides] [code] [blog]
Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level
ACL 2021, Findings
[paper] [slides] [code]
InCoder: A Generative Model for Code Infilling and Synthesis
Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, Mike Lewis
Meta-learning via Language Model In-context
Yanda Chen, Ruiqi Zhong, Sheng Zha, George
Karypis, He He
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
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
NeurIPS 2021 Workshop on Distribution Shifts
Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Kristy Lee, Zheng Zhang,
EMNLP 2021, Findings
Semantic Evaluation for Text-to-SQL with Distilled Test Suites
[paper] [slides] [code]
Semantic Scaffolds for Pseudocode-to-Code
Ruiqi Zhong, Mitchell Stern, Dan Klein
[paper] [slides] [code] [video]
Detecting and Reducing Bias in a High Stakes Domain
Ruiqi Zhong, Yanda Chen, Desmond Patton, Charlotte Selous, Kathy
[paper] [poster] [code]
Fine-grained Sentiment Analysis with Faithful
Ruiqi Zhong, Steven Shao, Kathy McKeown
Detecting Gang-involved Escalation on Social
Media Using Context
Serina Chang, Ruiqi Zhong, Ethan Adams, Fei-Tzin Lee, Siddharth
Varia, Desmond Patton, William Frey, Chris Kedzie, Kathy McKeown
Subspace Embedding and Linear Regression with
Alexandr Andoni, Chengyu Lin, Ying Sheng, Peilin Zhong,
[paper] [video] [slides]
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
- I represented Columbia University in ACM-ICPC and
Putnam Math Competition during my Sophormore year
(though it seems I was the bottleneck of our teams).
- I sleep at 11 p.m. and do not respond to later messages. Sometimes, however, I am actually awake; but I pretend not to see them anyways.
- My favorite animation character and role model is
Wenli Yang in Legend of Galactical Heroes.
- Berkeley Graduate Student Fellowship
- Theodore R. Bashkow Award (research), Academic Excellence Award (GPA)
- CRA Outstanding Undergraduate Research Award
Honorable Mention * 2 (2018, 2019)
- William Lowell Putnam Math Competition top 5% * 3
(2015, 2016, 2018)
Yes, I have a serious commitment towards cultivating future
researchers and practitioners who understand AI,
expand scientific knowledge,
and make the world a better place.
I sometimes spend ~3 hours per week with each undergrad whom I
Feel free to reach out if you satisfy any of the following
condition, and I would love to chat about opportunities.
Undergrads that I have mentored:
- Is passionate about NLP.
This is usually evidenced by
1) taking an NLP class,
2) playing around with NLP models on your own, or
3)(self-)learning a substantial fraction of material
- Has a strong intellectual interest in social
sciences or philosophy.
- Is from a developing country under-represented in
the research community.
- Excels at competitive programming or math olympiads.
- Xinyi Han (now Ph.D. at MIT)
- Yanda Chen (now Ph.D. at Columbia)
- Charlie Snell (prospective Ph.D. at UC Berkeley)
- Dhruba Ghosh (prospective Ph.D. at UW)
- Sicheng Tang
- Kristy Lee
- Zheng Zhang
- Harry Zhao
- Dong Yang
- Peter Zhang
- Oscar Xu
- Steve Li
- JinWoo Ahn