Ben Athiwaratkun

1.4k citations
13 papers · 633 · h-index 8

Impact in

    • Topic Modeling
    • Natural Language Processing Techniques
    • Sentiment Analysis and Opinion Mining
    • Domain Adaptation and Few-Shot Learning
    • Text and Document Classification Technologies
    • Advanced Text Analysis Techniques
    • Advanced Malware Detection Techniques

Papers in

    • Topic Modeling 6
    • Natural Language Processing Techniques 6
    • Domain Adaptation and Few-Shot Learning 2
    • Machine Learning and Data Classification 2
    • Sentiment Analysis and Opinion Mining 1
    • Advanced Neural Network Applications 2
    • Multimodal Machine Learning Applications 2

Ben Athiwaratkun

11 papers receiving 611 citations

Peers

Ben Athiwaratkun
Comparison fields: 5 of 81
  • Artificial Intelligence 497
  • Signal Processing 131
  • Computer Vision and Pattern Recognition 128
  • Software 21
  • Computer Networks and Communications 114
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Mahmood Yousefi‐Azar Australia
Jingbo Zhu China
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Ben Athiwaratkun relative to Jiahao Liu China Jiahao Liu's profile →
Citations per field
00.5×4.1×
Jiahao Liu · 1×
Citations per year

Countries citing papers authored by Ben Athiwaratkun

Since Specialization
Citations

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

Fields of papers citing papers by Ben Athiwaratkun

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

13 of 13 papers shown
#Work
1 2017181
2 2018170
3 2018101
4 201863
5 201746
6 202044
7 202314
8
Improving Consistency-Based Semi-Supervised Learning with Weight Averaging.
20188
9 20242
10 20182
11 20212
12 20240
13 20240

About Ben Athiwaratkun

Ben Athiwaratkun is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Computer Networks and Communications and Mathematical Physics, having authored 13 papers that have together received 633 indexed citations. Recurring topics across this work include Topic Modeling (6 papers), Natural Language Processing Techniques (6 papers), Domain Adaptation and Few-Shot Learning (2 papers), Machine Learning and Data Classification (2 papers), Advanced Neural Network Applications (2 papers), Multimodal Machine Learning Applications (2 papers), Advanced Topology and Set Theory (1 paper) and Sentiment Analysis and Opinion Mining (1 paper). The work is most often cited by research in Artificial Intelligence (497 citations), Signal Processing (131 citations), Computer Vision and Pattern Recognition (128 citations), Software (21 citations) and Computer Networks and Communications (114 citations). Ben Athiwaratkun has collaborated with scholars based in United States. Frequent co-authors include Jack W. Stokes, Andrew Gordon Wilson, Kilian Q. Weinberger, Xilun Chen, Yu Sun, Claire Cardie, Anima Anandkumar, Pavel Izmailov, Marc Finzi and Bing Xiang. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Studia Mathematica, arXiv (Cornell University) and Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing.

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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