Xiujun Li

180 papers receiving 3.7k citations

Hit Papers

VinVL: Revisiting Visual Representations in Vision-Language Models 2021 · 568 citations
5682021202620222024100200300400500

Peers

Xiujun Li
Comparison fields: 5 of 187
  • Computer Vision and Pattern Recognition 844
  • Soil Science 365
  • Infectious Diseases 493
  • Artificial Intelligence 844
  • Modeling and Simulation 110
Replace Kun Chen with:
Kun Chen China
Pengwei Hu China
Miron B. Kursa Poland
Kim‐Anh Lê Cao Australia
Cesare Furlanello Italy
Daniel J. Stekhoven Switzerland
Héctor Corrada Bravo United States
Edoardo Pasolli Italy
Kang Ning China
Fengzhu Sun United States
Xiujun Li relative to Kun Chen China Kun Chen's profile →
Citations per field
00.5×5.4×
Kun Chen · 1×
Citations per year

Countries citing papers authored by Xiujun Li

Since Specialization
Citations

This map shows the geographic impact of Xiujun Li's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Xiujun Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiujun Li more than expected).

Fields of papers citing papers by Xiujun Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xiujun Li. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Xiujun Li. The network helps show where Xiujun Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Xiujun Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Xiujun Li Line = papers co-authored together Xiujun Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 193 papers — load more, or switch the sort, to bring in the rest.

#Work
1
VinVL: Revisiting Visual Representations in Vision-Language Models
Hit paper breakdown →
2021568
2 2020151
3 2017127
4 2012120
5 2018100
6 202094
7 201993
8 201584
9 202077
10 201176
11 200357
12 201355
13 201353
14 201652
15 199551
16
VinVL: Making Visual Representations Matter in Vision-Language Models
202148
17 201448
18 201948
19 201344
20 201843

About Xiujun Li

Xiujun Li is a scholar working on Infectious Diseases, Cognitive Neuroscience, Epidemiology, Health, Toxicology and Mutagenesis and Ecology, having authored 193 papers that have together received 3.8k indexed citations. Recurring topics across this work include Viral Infections and Vectors (18 papers), Climate Change and Health Impacts (16 papers), Neurobiology of Language and Bilingualism (15 papers), Reading and Literacy Development (13 papers), Soil Carbon and Nitrogen Dynamics (11 papers), COVID-19 epidemiological studies (11 papers), Coastal wetland ecosystem dynamics (10 papers) and Air Quality and Health Impacts (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (844 citations), Soil Science (365 citations), Infectious Diseases (493 citations), Artificial Intelligence (844 citations) and Modeling and Simulation (110 citations). Xiujun Li has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Jianfeng Gao, Yejin Choi, Pengchuan Zhang, Jianwei Yang, Lei Zhang, Lijuan Wang, Xiaowei Hu, Chunyuan Li, Chunjie Tian and Lei Tian. Their work appears in journals such as PLoS ONE, International Journal of Environmental Research and Public Health, Chinese Geographical Science, PLoS neglected tropical diseases and Scientific Reports.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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