Qiaolin Xia

449 citations
7 papers · 197 · h-index 5

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Domain Adaptation and Few-Shot Learning
    • Speech and dialogue systems
    • Advanced Text Analysis Techniques
    • Text Readability and Simplification
    • Multimodal Machine Learning Applications
    • Advanced Image and Video Retrieval Techniques

Papers in

    • Natural Language Processing Techniques 4
    • Topic Modeling 4
    • Text Readability and Simplification 3
    • Advanced Text Analysis Techniques 1
    • Text and Document Classification Technologies 1
    • Multimodal Machine Learning Applications 1
    • Image and Video Quality Assessment 1

Qiaolin Xia

7 papers receiving 187 citations

Peers

Qiaolin Xia
Comparison fields: 5 of 19
  • Artificial Intelligence 185
  • Computer Vision and Pattern Recognition 87
  • Information Systems 13
  • Marketing 5
  • Developmental Biology 1
Replace Silvan Heller with:
Silvan Heller Switzerland
Rongxiang Weng China
Yinpei Dai China
Ke Tran Netherlands
Max Glockner Germany
Tagyoung Chung United States
Shexia He China
Florian Spieß Switzerland
Andrew Drozdov United States
Thomas Scialom France
Qiaolin Xia relative to Silvan Heller Switzerland Silvan Heller's profile →
Citations per field
00.5×10×15×17.5×
Silvan Heller · 1×
Citations per year

Countries citing papers authored by Qiaolin Xia

Since Specialization
Citations

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

Fields of papers citing papers by Qiaolin Xia

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Qiaolin Xia, 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 Qiaolin Xia Line = papers co-authored together Qiaolin Xia links everyone, so they are left out of the graph.

All Works

About Qiaolin Xia

Qiaolin Xia is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Sociology and Political Science, Information Systems and Infectious Diseases, having authored 7 papers that have together received 197 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (4 papers), Topic Modeling (4 papers), Text Readability and Simplification (3 papers), Multimodal Machine Learning Applications (1 paper), Image and Video Quality Assessment (1 paper), Digital Marketing and Social Media (1 paper), Advanced Text Analysis Techniques (1 paper) and Text and Document Classification Technologies (1 paper). The work is most often cited by research in Artificial Intelligence (185 citations), Computer Vision and Pattern Recognition (87 citations), Information Systems (13 citations), Marketing (5 citations) and Developmental Biology (1 citation). Qiaolin Xia has collaborated with scholars based in China and United States. Frequent co-authors include Zhifang Sui, Baobao Chang, Fuli Luo, Tianyu Liu, Yonatan Bisk, Jianfeng Gao, Yejin Choi, Xiujun Li, Chunyuan Li and Noah A. Smith. Their work appears in journals such as 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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