Ruiying Geng

627 citations
11 papers · 281 indexed · h-index 6
Topics
Topic Modeling (9 papers)Natural Language Processing Techniques (6 papers)Text and Document Classification Technologies (3 papers)
Journals
Transactions of the Association for Computational LinguisticsarXiv (Cornell University)Findings of the Association for Computational Linguistics: ACL 2022
Partner nations
ChinaCanadaUnited States

In The Last Decade

Ruiying Geng

9 papers receiving 273 citations

Peers

Ruiying Geng
Comparison fields: 5 of 37
  • Artificial Intelligence 269
  • Computer Vision and Pattern Recognition 70
  • Information Systems 24
  • Management Science and Operations Research 10
  • Computer Networks and Communications 9
Replace Guanghui Qin with:
Guanghui Qin United States
Lintang Sutawika United States
Hidetaka Kamigaito Japan
Ehsan Shareghi Australia
Scott Yih United States
Shuangzhi Wu China
Sho Takase Japan
Chunting Zhou United States
Ruiying Geng relative to Guanghui Qin United States Guanghui Qin's profile →
Citations per field
00.5×10.5×
Guanghui Qin · 1×
Citations per year

Countries citing papers authored by Ruiying Geng

Since Specialization
Citations

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

Fields of papers citing papers by Ruiying Geng

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruiying Geng

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 3
2 0
3 1
4 0
5 6
6 26
7 45
8 55
9
Few-Shot Text Classification with Induction Network.
9
10 131
11 5

About Ruiying Geng

Ruiying Geng is a scholar working on General Social Sciences, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 281 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Natural Language Processing Techniques (6 papers) and Text and Document Classification Technologies (3 papers). The work is most often cited by research in Artificial Intelligence (269 citations), Computer Vision and Pattern Recognition (70 citations) and General Social Sciences (4 citations). Ruiying Geng has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Jian Sun, Binhua Li, Xiaodan Zhu, Yongbin Li, Ping Jian, Fei Huang, Luo Si, Qiao Liu, Hao Wang and Yang Li. Their work appears in journals such as Transactions of the Association for Computational Linguistics, arXiv (Cornell University) and Findings of the Association for Computational Linguistics: ACL 2022.

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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