Lujing Xie: h-index, Total Citations, and Citation Map
Lujing Xie's h-index is 3 (2 i10-index, 130+ total citations across 4+ publications) according to Google Scholar as of May 2026. Lujing Xie is affiliated with Peking University.
Lujing Xie is a researcher affiliated with Peking University, specializing in Semi-Supervised Learning. Their work has been cited 130 times. This profile visualizes their global influence, highlighting strong citation networks in China.
Lujing Xie's Citation Metrics
Bibliometric impact based on 4 indexed publications.
- H-Index
- 3
- i10-Index
- 2
- Total Citations
- 130
- Citing Countries
- 10
As of May 2026.
Lujing Xie has an h-index of 3 and 130 total citations across 4 publications, with research cited by institutions in 10 countries.
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Global Impact Map
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Top Cited Works
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Mmvu: Measuring expert-level multi-discipline video understanding
202598
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.
24 citing papers could not be classified (no author data) — excluded from the percentages above.
The researcher developed Bacon, a balanced feature-level contrastive learning framework that boosts imbalanced semi-supervised learning, establishing a novel approach to handling class imbalance in low-label regimes.
The researcher established a rigorous benchmark for evaluating expert-level, multi-disciplinary video understanding, creating a foundational standard for assessing advanced AI capabilities in complex visual domains.
Citation trend (last 10 years)Click to expand
Citation Trend (Last 10 Years)
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