Junnan Li

1.8k citations
29 papers · 668 · 1 hit paper · h-index 13

Impact in

Papers in

Junnan Li

26 papers receiving 656 citations

Junnan Li's Hit Papers

CodeT5+: Open Code Large Language Models for Code Understanding and Generation 2023 · 159 citations
1590+1+2Years since publication50100150

Peers

Junnan Li
Comparison fields: 5 of 83
  • Software 64
  • Computer Vision and Pattern Recognition 198
  • Artificial Intelligence 291
  • Pollution 100
  • Industrial and Manufacturing Engineering 54
Replace Zhiqiang Wang with:
Zhiqiang Wang China
Awni Hammouri Jordan
Saptarshi Sengupta United States
Bruno Baruque Spain
Xuelian Deng China
Haobo Wang China
Zhi Zeng China
Crefeda Faviola Rodrigues United Kingdom
Junnan Li relative to Zhiqiang Wang China Zhiqiang Wang's profile →
Citations per field
00.5×20×40×54×
Zhiqiang Wang · 1×
Citations per year

Countries citing papers authored by Junnan Li

Since Specialization
Citations

This map shows the geographic impact of Junnan 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 Junnan Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Junnan Li more than expected).

Fields of papers citing papers by Junnan Li

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Junnan 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 Junnan Li. The network helps show where Junnan Li may publish in the future.

Co-authors

The 25 scholars most cited alongside Junnan 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 Junnan Li Line = papers co-authored together Junnan Li links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1
CodeT5+: Open Code Large Language Models for Code Understanding and Generation
Hit paper breakdown →
2023159
2 2021159
3 202152
4 202343
5 201733
6 202230
7 201929
8
Unsupervised Learning of View-invariant Action Representations
201821
9 202221
10 202016
11 201813
12 202012
13 201812
14 202012
15 202011
16 20237
17 20236
18 20206
19 20206
20 20225

About Junnan Li

Junnan Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Information Systems and Pollution, having authored 29 papers that have together received 668 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (6 papers), Multimodal Machine Learning Applications (5 papers), Advanced Neural Network Applications (5 papers), Video Surveillance and Tracking Methods (4 papers), Human Pose and Action Recognition (4 papers), Caching and Content Delivery (3 papers), Gait Recognition and Analysis (3 papers) and Microplastics and Plastic Pollution (3 papers). The work is most often cited by research in Software (64 citations), Computer Vision and Pattern Recognition (198 citations), Artificial Intelligence (291 citations), Pollution (100 citations) and Industrial and Manufacturing Engineering (54 citations). Junnan Li has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Steven C. H. Hoi, Caiming Xiong, Yue Wang, Akhilesh Deepak Gotmare, Hung Lê, Mohan Kankanhalli, Yiliang He, Yongkang Wong, Karina Yew‐Hoong Gin and Mui‐Choo Jong. Their work appears in journals such as Future Generation Computer Systems, Electronics, Journal of Parallel and Distributed Computing, IEEE Robotics and Automation Letters and PeerJ Computer Science.

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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