Yejin Choi Google Scholar: h-index, Total Citations, and Citation Map
Yejin Choi's h-index is 141 (413 i10-index, 100,770+ total citations across 646+ publications) according to Google Scholar as of October 2026. Yejin Choi is affiliated with Stanford University / NVIDIA.
Yejin Choi is a researcher affiliated with Stanford University / NVIDIA, specializing in Natural Language Processing, Deep Learning, Artificial Intelligence. Their work has been cited 100,770 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Yejin Choi's Citation Metrics
Bibliometric impact based on 646 indexed publications.
- H-Index
- 141
- i10-Index
- 413
- Total Citations
- 100,770
- Citing Countries
- 82
As of October 2026.
Yejin Choi has an h-index of 141 and 100,770 total citations across 646 publications, with research cited by institutions in 82 countries.
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Global Impact Map
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The curious case of neural text degeneration
20195,359
Top Citing Countries
Top Citing Institutions
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Significant Contributions
Auto-detected research lines — a seminal paper and the follow-up work building on it. Review and edit before using in a petition. Each Free PDF opens in a new tab — EB-1A organises this into the structure USCIS applies to Criterion 5 of 8 CFR § 204.5(h)(3)(v); EB-1B re-frames it under § 204.5(i)(3) (outstanding researcher); NIW presents it under prong 2 of Matter of Dhanasar.
1271 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered the analysis of neural text degeneration, establishing a foundational framework for evaluating and mitigating toxic outputs in language models through decoding-time control mechanisms.
The researcher advanced self-learning frameworks beyond math reasoning and developed efficient hybrid models for agentic reasoning, establishing a foundational line of work in scalable AI systems.
The researcher developed a seminal framework for detecting deceptive opinion spam, establishing a foundational approach that has been widely adopted by the independent academic community.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Yejin Choi's research
Yejin Choi is a researcher in Natural Language Processing, Deep Learning and Artificial Intelligence at Stanford University / NVIDIA. Their work has been cited 100,770 times across 646 publications (h-index 141), according to Google Scholar.
Their most-cited work, “The curious case of neural text degeneration” (2019), has accumulated 5,359 citations. Other influential works include “Hellaswag: Can a machine really finish your sentence?” (2019) with 4,838 citations and “Winogrande: An adversarial winograd schema challenge at scale” (2021) with 3,775 citations.
Citations of Yejin Choi's research come primarily from United States, China and United Kingdom, reflecting international research impact across 5+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
