Zewen Chi

1.2k citations
16 papers · 416 · h-index 7

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Speech Recognition and Synthesis
    • Domain Adaptation and Few-Shot Learning
    • Advanced Text Analysis Techniques
    • Text Readability and Simplification
    • Multimodal Machine Learning Applications

Papers in

Zewen Chi

15 papers receiving 404 citations

Peers

Zewen Chi
Comparison fields: 5 of 39
  • Artificial Intelligence 361
  • Computer Vision and Pattern Recognition 148
  • Information Systems 56
  • Health Informatics 3
  • General Social Sciences 5
Replace Scott Yih with:
Scott Yih United States
Rushin Shah United States
Chunting Zhou United States
Ruiying Geng China
Sho Takase Japan
Zhongjun He China
Yichen Jiang United States
Hidetaka Kamigaito Japan
Myung-Gil Jang South Korea
Amir Kantor Israel
Zewen Chi relative to Scott Yih United States Scott Yih's profile →
Citations per field
00.5×20×40×51×
Scott Yih · 1×
Citations per year

Countries citing papers authored by Zewen Chi

Since Specialization
Citations

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

Fields of papers citing papers by Zewen Chi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 2021143
2 202070
3 202147
4 202240
5 202136
6 202132
7 202120
8 20236
9 20236
10 20226
11 20244
12 20202
13 20242
14 20231
15 20221
16 20230

About Zewen Chi

Zewen Chi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems and General Social Sciences, having authored 16 papers that have together received 416 indexed citations. Recurring topics across this work include Topic Modeling (15 papers), Natural Language Processing Techniques (14 papers), Speech Recognition and Synthesis (5 papers), Multimodal Machine Learning Applications (4 papers), Speech and dialogue systems (2 papers), Biomedical Text Mining and Ontologies (2 papers), Advanced Text Analysis Techniques (1 paper) and Advanced Graph Neural Networks (1 paper). The work is most often cited by research in Artificial Intelligence (361 citations), Computer Vision and Pattern Recognition (148 citations), Information Systems (56 citations), Health Informatics (3 citations) and General Social Sciences (5 citations). Zewen Chi has collaborated with scholars based in China, United States and India. Frequent co-authors include Heyan Huang, Xian-Ling Mao, Furu Wei, Li Dong, Saksham Singhal, Song Xia, Wenhui Wang, Shaohan Huang, Ming Zhou and Nan Yang. Their work appears in journals such as Information Sciences, Information Processing & Management, IEEE/ACM Transactions on Audio Speech and Language Processing, Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval and Proceedings of the AAAI Conference on Artificial Intelligence.

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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