Xuechen Li: h-index, Total Citations, and Citation Map
Xuechen Li's h-index is 21 (22 i10-index, 24,101+ total citations across 5+ publications) according to Google Scholar as of May 2026. Xuechen Li is affiliated with Unknown affiliation.
Xuechen Li is a researcher affiliated with Unknown affiliation, specializing in machine learning, artificial intelligence, statistics. Their work has been cited 24,101 times. This profile visualizes their global influence, highlighting strong citation networks in United States.
Xuechen Li's Citation Metrics
Bibliometric impact based on 5 indexed publications.
- H-Index
- 21
- i10-Index
- 22
- Total Citations
- 24,101
- Citing Countries
- 17
As of May 2026.
Xuechen Li has an h-index of 21 and 24,101 total citations across 5 publications, with research cited by institutions in 17 countries.
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We've mapped 5,000 of 24,101 citations for Xuechen Li
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Global Impact Map
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Top Cited Works
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On the opportunities and risks of foundation models
20219,571
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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.
The researcher provided a seminal framework for evaluating the dual implications of foundation models, establishing a critical reference point for assessing their societal impact and technical potential.
The researcher advanced variational autoencoder theory by isolating specific sources of disentanglement, a foundational contribution evidenced by nearly 1,900 citations from independent scholars.
The researcher established a holistic evaluation framework for language models, providing a comprehensive benchmark that has become a standard reference in the field.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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