Yiming Lin: h-index, Total Citations, and Citation Map
Yiming Lin's h-index is 9 (9 i10-index, 328+ total citations across 21+ publications) according to Google Scholar as of June 2026. Yiming Lin is affiliated with UC Berkeley.
Yiming Lin is a researcher affiliated with UC Berkeley, specializing in Data Management, Data Quality, Unstructured Data Exploration. Their work has been cited 328 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Yiming Lin's Citation Metrics
Bibliometric impact based on 21 indexed publications.
- H-Index
- 9
- i10-Index
- 9
- Total Citations
- 328
- Citing Countries
- 18
As of June 2026.
Yiming Lin has an h-index of 9 and 328 total citations across 21 publications, with research cited by institutions in 18 countries.
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Querying templatized document collections with large language models
202568
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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.
10 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher pioneered methods for synthesizing data quality assertions in LLM pipelines, establishing a framework for proactive data systems that has garnered significant independent academic attention.
The researcher advanced methods for querying templatized document collections using large language models, establishing a foundational approach adopted by independent scholars.
The researcher developed a framework for selecting data sources to facilitate information integration within the complex and high-volume environments characteristic of the big data era.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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