Hannaneh Hajishirzi Google Scholar: h-index, Total Citations, and Citation Map
Hannaneh Hajishirzi's h-index is 106 (216 i10-index, 71,600+ total citations across 308+ publications) according to Google Scholar as of November 2026. Hannaneh Hajishirzi is affiliated with University of Washington; Allen AI.
Hannaneh Hajishirzi is a researcher affiliated with University of Washington; Allen AI, specializing in various fields. Their work has been cited 71,600 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Hannaneh Hajishirzi's Citation Metrics
Bibliometric impact based on 308 indexed publications.
- H-Index
- 106
- i10-Index
- 216
- Total Citations
- 71,600
- Citing Countries
- 74
As of November 2026.
Hannaneh Hajishirzi has an h-index of 106 and 71,600 total citations across 308 publications, with research cited by institutions in 74 countries.
Download Exports (PNG, CSV, Poster)
Free Viewing Hannaneh Hajishirzi's citation map is always free. Pay once to download poster, PNG, and CSV files for offline use or your visa packet.
Showing partial map from open academic databases
Upgrade ($39.98) for the complete Google Scholar crawl.
Global Impact Map
Visualizing the geographic distribution of institutions that have cited your work.
Starting…
Pins will appear here as institutions are resolved — no need to refresh.
Self-instruct: Aligning language models with self-generated instructions
20234,130
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)
Related Guides
Learn how to use citation maps for your research and visa applications.
About Hannaneh Hajishirzi's research
Hannaneh Hajishirzi is a researcher at University of Washington; Allen AI. Their work has been cited 71,600 times across 308 publications (h-index 106), according to Google Scholar.
Their most-cited work, “Self-instruct: Aligning language models with self-generated instructions” (2023), has accumulated 4,130 citations. Other influential works include “Self-rag: Learning to retrieve, generate, and critique through self-reflection” (2024) with 3,470 citations and “Beyond the imitation game: Quantifying and extrapolating the capabilities of language models” (2022) with 3,062 citations.
Citations of Hannaneh Hajishirzi'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.
