Percy Liang: h-index, Total Citations, and Citation Map
Percy Liang's h-index is 141 (351 i10-index, 157,760+ total citations across 497+ publications) according to Google Scholar as of September 2026. Percy Liang is affiliated with Professor of Computer Science, Stanford University.
Percy Liang is a researcher affiliated with Professor of Computer Science, Stanford University, specializing in machine learning, natural language processing. Their work has been cited 157,760 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Percy Liang's Citation Metrics
Bibliometric impact based on 497 indexed publications.
- H-Index
- 141
- i10-Index
- 351
- Total Citations
- 157,760
- Citing Countries
- 88
As of September 2026.
Percy Liang has an h-index of 141 and 157,760 total citations across 497 publications, with research cited by institutions in 88 countries.
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Global Impact Map
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Squad: 100,000+ questions for machine comprehension of text
201612,189
Top Citing Countries
Top Citing Institutions
Visa Evidence Package
Views and exports tuned for EB-1A, O-1A, and EB-2 NIW petitions. Sustained acclaim, geographic reach, and independent-citation filtering are the strongest evidence categories immigration adjudicators look for.
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.
1468 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher established foundational benchmarks for machine comprehension and advanced the holistic evaluation of language model capabilities, driving significant independent adoption in the field.
The researcher pioneered methods for integrating knowledge graphs with language models to enhance reasoning capabilities in question answering systems.
The researcher pioneered certified defenses against adversarial examples, establishing a foundational framework for verifying neural network robustness through rigorous mathematical guarantees.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Percy Liang's research
Percy Liang is a researcher in machine learning and natural language processing at Professor of Computer Science, Stanford University. Their work has been cited 157,760 times across 497 publications (h-index 141), according to Google Scholar.
Their most-cited work, “Squad: 100,000+ questions for machine comprehension of text” (2016), has accumulated 12,189 citations. Other influential works include “On the opportunities and risks of foundation models” (2021) with 11,298 citations and “Prefix-tuning: Optimizing continuous prompts for generation” (2021) with 7,619 citations.
Citations of Percy Liang'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.
