Guanghui Qin

453 citations
10 papers · 254 indexed · 1 hit paper · h-index 6
Topics
Topic Modeling (5 papers)Natural Language Processing Techniques (5 papers)Protein Kinase Regulation and GTPase Signaling (2 papers)

In The Last Decade

Guanghui Qin

8 papers receiving 244 citations

Hit Papers

Learning How to Ask: Querying LMs with Mixtures of Soft P...2021202620222024202150100150200

Peers

Guanghui Qin
Comparison fields: 5 of 44
  • Artificial Intelligence 223
  • Computer Vision and Pattern Recognition 63
  • Information Systems 28
  • Molecular Biology 8
  • Computer Networks and Communications 6
Replace Naveen Arivazhagan with:
Naveen Arivazhagan United States
Johnny Tian-Zheng Wei United States
Jon Saad-Falcon United States
Koustuv Sinha Canada
Avi Caciularu Israel
Jianshu Ji China
Lintang Sutawika United States
Jasmijn Bastings United States
Guanghui Qin relative to Naveen Arivazhagan United States Naveen Arivazhagan's profile →
Citations per field
00.5×1.5×1.8×
Naveen Arivazhagan · 1×
Citations per year

Countries citing papers authored by Guanghui Qin

Since Specialization
Citations

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

Fields of papers citing papers by Guanghui Qin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guanghui Qin

This figure shows the co-authorship network connecting the top 25 collaborators of Guanghui Qin. A scholar is included among the top collaborators of Guanghui Qin 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 Guanghui Qin. Guanghui Qin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

10 of 10 papers shown
#WorkIndexed citations
1 0
2 0
3 5
4 7
5 1
6
Learning How to Ask: Querying LMs with Mixtures of Soft Promptsbreakdown →
210
7 11
8 4
9 11
10 5

About Guanghui Qin

Guanghui Qin is a scholar working on Artificial Intelligence, Cell Biology and Law, having authored 10 papers that have together received 254 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers) and Protein Kinase Regulation and GTPase Signaling (2 papers). The work is most often cited by research in Artificial Intelligence (223 citations), Health Informatics (5 citations) and Computer Vision and Pattern Recognition (63 citations). Guanghui Qin has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Jason Eisner, Chin-Yew Lin, Benjamin Van Durme, Jin-Ge Yao, Jinpeng Wang, Yukun Feng, Craig Harman, Dhiman Sankar Pal, Tongfei Chen and Peter N. Devreotes. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Cell Biology and arXiv (Cornell University).

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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