Nayeon Lee

1.0k total citations · 1 hit paper
6 papers, 417 citations indexed

About

Nayeon Lee is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Nayeon Lee has authored 6 papers receiving a total of 417 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Information Systems and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Nayeon Lee's work include Multimodal Machine Learning Applications (2 papers), Natural Language Processing Techniques (2 papers) and Topic Modeling (2 papers). Nayeon Lee is often cited by papers focused on Multimodal Machine Learning Applications (2 papers), Natural Language Processing Techniques (2 papers) and Topic Modeling (2 papers). Nayeon Lee collaborates with scholars based in South Korea and Hong Kong. Nayeon Lee's co-authors include Tiezheng Yu, Ziwei Ji, Pascale Fung, Bryan Wilie, Yejin Bang, Holy Lovenia, Samuel Cahyawijaya, Willy Chung, Yan Xu and Wenliang Dai and has published in prestigious journals such as Transactions of the Association for Computational Linguistics, Rare & Special e-Zone (The Hong Kong University of Science and Technology) and Journal of Communication Science.

In The Last Decade

Nayeon Lee

6 papers receiving 402 citations

Hit Papers

A Multitask, Multilingual, Multimodal Evaluation of ChatG... 2023 2026 2024 2025 2023 100 200 300

Peers

Nayeon Lee
Comparison fields: 5 of 84
  • Artificial Intelligence 280
  • Health Informatics 79
  • Information Systems 61
  • Sociology and Political Science 32
  • Computer Science Applications 28
Replace Willy Chung with:
Willy Chung Hong Kong
Holy Lovenia Hong Kong
Yejin Bang Hong Kong
Bryan Wilie Hong Kong
Arkadiusz Janz Poland
Kamil Kanclerz Poland
Julita Bielaniewicz Poland
Bartłomiej Koptyra Poland
Konrad Wojtasik Poland
Łukasz Radliński Poland
Willy Chung Hong Kong View profile →
Citations per field, relative to Nayeon Lee
Nayeon Lee · 1×
Citations per year, relative to Nayeon Lee
Nayeon Lee · 1×

Countries citing papers authored by Nayeon Lee

Since Specialization
Citations

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

Fields of papers citing papers by Nayeon Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nayeon Lee

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

All Works

6 of 6 papers shown
# Work Indexed citations
1 3
2 8
3 16
4
A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity breakdown →
388
5 1
6 1

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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2026