Yen-Chun Chen
- Artificial Intelligence top 2%
- Computer Vision and Pattern Recognition top 5%
- Information Systems
- Molecular Biology
- Political Science and International Relations
- Co-authors
- Mohit BansalZhe GanLinjie LiYu ChengJingjing LiuFaisal AhmedAhmed El KholyLicheng Yu
- Topics
- Multimodal Machine Learning Applications (9 papers)Topic Modeling (6 papers)Domain Adaptation and Few-Shot Learning (5 papers)
- Journals
- Applied Physics LettersOptics & Laser TechnologyarXiv (Cornell University)
- Partner nations
- United StatesTaiwanFinland
In The Last Decade
Yen-Chun Chen
12 papers receiving 653 citations
Hit Papers
Peers
Comparison fields: 5 of 54
- Artificial Intelligence 610
- Computer Vision and Pattern Recognition 302
- Information Systems 30
- Molecular Biology 22
- Political Science and International Relations 12
Countries citing papers authored by Yen-Chun Chen
This map shows the geographic impact of Yen-Chun Chen'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 Yen-Chun Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yen-Chun Chen more than expected).
Fields of papers citing papers by Yen-Chun Chen
This network shows the impact of papers produced by Yen-Chun Chen. 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 Yen-Chun Chen. The network helps show where Yen-Chun Chen may publish in the future.
Co-authorship network of co-authors of Yen-Chun Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Yen-Chun Chen. A scholar is included among the top collaborators of Yen-Chun Chen 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 Yen-Chun Chen. Yen-Chun Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 19 | |
| 5 | VALUE: A Multi-Task Benchmark for Video-and-Language Understanding Evaluation | 1 |
| 6 | 53 | |
| 7 | 11 | |
| 8 | 76 | |
| 9 | Large-Scale Adversarial Training for Vision-and-Language Representation Learning | 15 |
| 10 | Distilling the Knowledge of BERT for Text Generation | 12 |
| 11 | UNITER: Learning UNiversal Image-TExt Representations | 166 |
| 12 | Fast Abstractive Summarization with Reinforce-Selected Sentence Rewritingbreakdown → | 329 |
About Yen-Chun Chen
Yen-Chun Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Surfaces, Coatings and Films, having authored 12 papers that have together received 688 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (9 papers), Topic Modeling (6 papers) and Domain Adaptation and Few-Shot Learning (5 papers). The work is most often cited by research in Artificial Intelligence (610 citations), Computer Vision and Pattern Recognition (302 citations) and Health Informatics (5 citations). Yen-Chun Chen has collaborated with scholars based in United States, Taiwan and Finland. Frequent co-authors include Mohit Bansal, Zhe Gan, Linjie Li, Yu Cheng, Jingjing Liu, Faisal Ahmed, Ahmed El Kholy, Licheng Yu, Jingzhou Liu and Cheng Yu. Their work appears in journals such as Applied Physics Letters, Optics & Laser Technology 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.