Yi Tay: h-index, Total Citations, and Citation Map
Yi Tay's h-index is 77 (123 i10-index, 72,352+ total citations across 144+ publications) according to Google Scholar as of July 2026. Yi Tay is affiliated with Research Scientist, Google DeepMind.
Yi Tay is a researcher affiliated with Research Scientist, Google DeepMind, specializing in large language models, machine learning, artificial general intelligence. Their work has been cited 72,352 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Yi Tay's Citation Metrics
Bibliometric impact based on 144 indexed publications. Of these, 16 are original research articles — the rest are literature highlights, conference abstracts or theses.
- H-Index
- 77
- i10-Index
- 123
- Total Citations
- 72,352
- Citing Countries
- 66
As of July 2026.
Yi Tay has an h-index of 77 and 72,352 total citations across 144 publications, with research cited by institutions in 66 countries.
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Global Impact Map
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Palm: Scaling language modeling with pathways
20239,784
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.
747 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher advanced multilingual chain-of-thought reasoning in language models, establishing a framework subsequently adopted in highly cited multimodal systems and rigorous benchmark evaluations.
The researcher advanced large-scale language modeling by introducing pathway-based scaling methods and extending these frameworks to instruction-finetuned models, establishing a foundational approach for efficient model development.
The researcher established a foundational benchmark for efficient Transformers and subsequently synthesized the field's progress through a highly cited comprehensive survey.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Yi Tay's research
Yi Tay is a researcher in large language models, machine learning and artificial general intelligence at Research Scientist, Google DeepMind. Their work has been cited 72,352 times across 144 publications (h-index 77), according to Google Scholar.
Their most-cited work, “Palm: Scaling language modeling with pathways” (2023), has accumulated 9,784 citations. Other influential works include “Gemini: a family of highly capable multimodal models” (2023) with 9,780 citations and “Emergent abilities of large language models” (2022) with 6,826 citations.
Citations of Yi Tay's research come primarily from China, United States 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.
