Amanda Askell Google Scholar: h-index, Total Citations, and Citation Map
Amanda Askell has 194,893+ total citations according to Google Scholar as of November 2026. Amanda Askell is affiliated with Anthropic.
Amanda Askell is a researcher affiliated with Anthropic, specializing in AI & Machine Learning. Their work has been cited 194,893 times. This profile visualizes their global influence, highlighting strong citation networks in United Kingdom.
Amanda Askell's Citation Metrics
Bibliometric impact based on 1 indexed publication.
- H-Index
- 1
- i10-Index
- 1
- Total Citations
- 194,893
- Citing Countries
- 4
As of November 2026.
Amanda Askell has an h-index of 1 and 194,893 total citations across 1 publication, with research cited by institutions in 4 countries.
Global Impact Map
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Language models are few-shot learners
202081,047
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.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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About Amanda Askell's research
Amanda Askell is a researcher in AI & Machine Learning at Anthropic. Their work has been cited 194,893 times across 1 publication, according to Google Scholar.
Their most-cited work, “Language models are few-shot learners” (2020), has accumulated 81,047 citations.
Citations of Amanda Askell's research come primarily from United Kingdom, United States and Canada, reflecting international research impact across 4+ countries. The interactive citation map above shows the full geographic distribution of the institutions citing this work.
