Lingpeng Kong

1.5k citations
28 papers · 544 indexed · h-index 11
Topics
Topic Modeling (12 papers)Natural Language Processing Techniques (11 papers)Multimodal Machine Learning Applications (6 papers)
Partner nations
ChinaHong KongDenmark

In The Last Decade

Lingpeng Kong

25 papers receiving 528 citations

Peers

Lingpeng Kong
Comparison fields: 5 of 99
  • Artificial Intelligence 204
  • Plant Science 192
  • Molecular Biology 122
  • Computer Vision and Pattern Recognition 87
  • Global and Planetary Change 21
Replace Mingjie Li with:
Mingjie Li China
Milan Gavrilović Serbia
Jiaqiang Wang China
Mayank Pandey India
Mariem Ben Abdallah Tunisia
Jianying Liu China
Günter Neumann Germany
Chloé Friguet France
Sofie Van Landeghem Belgium
Ahmed Sohaib Pakistan
Lingpeng Kong relative to Mingjie Li China Mingjie Li's profile →
Citations per field
00.5×5.3×
Mingjie Li · 1×
Citations per year

Countries citing papers authored by Lingpeng Kong

Since Specialization
Citations

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

Fields of papers citing papers by Lingpeng Kong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingpeng Kong

This figure shows the co-authorship network connecting the top 25 collaborators of Lingpeng Kong. A scholar is included among the top collaborators of Lingpeng Kong based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lingpeng Kong. Lingpeng Kong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 45
2 2
3 0
4 6
5 5
6 0
7 31
8 10
9 2
10 8
11 44
12 6
13 36
14 22
15 6
16 5
17
A Mutual Information Maximization Perspective of Language Representation Learning
18
18
Putting Machine Translation in Context with the Noisy Channel Model
1
19 10
20 0

About Lingpeng Kong

Lingpeng Kong is a scholar working on Artificial Intelligence, Biochemistry and Computer Vision and Pattern Recognition, having authored 28 papers that have together received 544 indexed citations. Recurring topics across this work include Topic Modeling (12 papers), Natural Language Processing Techniques (11 papers) and Multimodal Machine Learning Applications (6 papers). The work is most often cited by research in Artificial Intelligence (204 citations), Plant Science (192 citations) and Computer Vision and Pattern Recognition (87 citations). Lingpeng Kong has collaborated with scholars based in China, Hong Kong and Denmark. Frequent co-authors include Zhen Wu, Rong Zhou, Tongmin Zhao, Carl‐Otto Ottosen, Fangling Jiang, Chris Dyer, Xiaqing Yu, Noah A. Smith, Liping Zhao and Miguel Ballesteros. Their work appears in journals such as Molecules, BMC Bioinformatics and PLoS Computational Biology.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026