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Ruiqi Zhong

Ruiqi Zhong has 2 papers in our library, in 2022–2023, most of them on Language models & pretraining; often with Bailin Wang, Chien-Sheng Wu, Dan Klein.

2 papers in our library · 2022–2023

OpenAlex · ORCID · h-index 13 · 38 works · 934 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 1,083 times in our library · 18 more in our library without a page yet · ⭐ Paper Stars ranking: #4067

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓University of California, BerkeleyBerkeley · United States2018–2025 · 22 paperscurrent🏢AnthropicSan Francisco · United States2025 · 1 papercurrent🎓Columbia UniversityNew York · United States2018–2019 · 5 papers🎓Chinese Academy of Medical Sciences & Peking Union Medical CollegeBeijing · China2022 · 1 paperEducation · M.D

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📚 Shelves 7The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksComputer Vision and Pattern Recognition · 1 workGeneral Social Sciences · 1 workSocial Sciences · 1 work

🧭 Topics 1Research subjects and languages the work is about.Language models & pretraining · 1 work

 Works by year

2020s

20231 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models (2022 · 407 citations)
    Structured knowledge grounding (SKG) covers tasks where a system answers a user request by drawing on databases, knowledge graphs or tables.
  2. Goal Driven Discovery of Distributional Differences via Language Descriptions (2023 · 42 citations)
    Comparing two large text collections by hand is slow and ad hoc. The authors frame this as an ML task called D5. A system receives a user's exploration goal and a pair of corpora. It must return natural-language predicates that describe how the corpora differ in ways that matter for that goal. For example, reports…

All works

20 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Tianbao Xie, Chen Henry Wu, Peng Shi, et al.2022 · 407 citations
  2. InCoder: A Generative Model for Code Infilling and Synthesis ↗arXiv:2204.05999 · no summary yetDaniel Fried et al.2023 · 300 citations
  3. DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation ↗arXiv:2211.11501 · no summary yetYuhang Lai et al.2022 · 199 citations
  4. Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections ↗arXiv:2104.04670 · no summary yetRuiqi Zhong et al.2021 · 195 citations
  5. Semantic Evaluation for Text-to-SQL with Distilled Test Suites ↗Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) · no summary yetRuiqi Zhong, Tao Yu, Dan Klein2020 · 166 citations
  6. Meta-learning via Language Model In-context Tuning ↗arXiv:2110.07814 · no summary yetYanda Chen et al.2021 · 160 citations
  7. Foundational Challenges in Assuring Alignment and Safety of Large Language Models ↗arXiv:2404.09932 · no summary yetUsman Anwar et al.2024 · 87 citations
  8. Learning by Distilling Context ↗arXiv:2209.15189 · no summary yetCharlie Snell, Dan Klein, Ruiqi Zhong2022 · 67 citations
  9. Goal Driven Discovery of Distributional Differences via Language DescriptionsarXiv:2302.14233Ruiqi Zhong, Peter Zhang, Steve Li, et al.2023 · 42 citations
  10. Do Models Explain Themselves? Counterfactual Simulatability of Natural Language Explanations ↗arXiv (Cornell University) · no summary yetYanda Chen et al.2023 · 41 citations
  11. Are Larger Pretrained Language Models Uniformly Better? Comparing Performance at the Instance Level ↗Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 · no summary yetRuiqi Zhong et al.2021 · 39 citations
  12. Describing Differences between Text Distributions with Natural Language ↗arXiv (Cornell University) · no summary yetRuiqi Zhong et al.2022 · 34 citations
  13. Language Models Learn to Mislead Humans via RLHF ↗arXiv (Cornell University) · no summary yetJiaxin Wen et al.2024 · 33 citations
  14. Describing Differences in Image Sets with Natural Language ↗IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · no summary yetLisa Dunlap et al.2024 · 28 citations
  15. Semantic Scaffolds for Pseudocode-to-Code Generation ↗Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics · no summary yetRuiqi Zhong, Mitchell Stern, Dan Klein2020 · 24 citations
  16. Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQL ↗Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing · no summary yetRuiqi Zhong et al.2023 · 15 citations
  17. Article-Level Slant and Polarization of News Consumption on Social Media ↗SSRN Electronic Journal · no summary yetLuca Braghieri et al.2024 · 11 citations
  18. Explaining Datasets in Words: Statistical Models with Natural Language Parameters ↗neural information processing systems · no summary yetRuiqi Zhong et al.2024 · 9 citations
  19. Approximating How Single Head Attention Learns ↗arXiv (Cornell University) · no summary yetCharlie Snell et al.2021 · 5 citations
  20. The Effect of Model Size on Worst-Group Generalization ↗arXiv (Cornell University) · no summary yetAlan Pham et al.2021

 Co-authors here

12 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 1,083 times (of the 149,439 papers whose bibliographies we read); 192 citing papers with a page here →.

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