Hongyu Lin
- Artificial Intelligence top 2%
- Electrical and Electronic Engineering
- Biomedical Engineering
- Information Systems top 5%
- Management Science and Operations Research top 5%
- Topics
- Topic Modeling (23 papers)Natural Language Processing Techniques (23 papers)Multimodal Machine Learning Applications (6 papers)
- Partner nations
- ChinaTaiwanUnited States
In The Last Decade
Hongyu Lin
50 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 119
- Artificial Intelligence 742
- Electrical and Electronic Engineering 185
- Biomedical Engineering 158
- Information Systems 129
- Management Science and Operations Research 116
Countries citing papers authored by Hongyu Lin
This map shows the geographic impact of Hongyu Lin'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 Hongyu Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongyu Lin more than expected).
Fields of papers citing papers by Hongyu Lin
This network shows the impact of papers produced by Hongyu Lin. 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 Hongyu Lin. The network helps show where Hongyu Lin may publish in the future.
Co-authorship network of co-authors of Hongyu Lin
This figure shows the co-authorship network connecting the top 25 collaborators of Hongyu Lin. A scholar is included among the top collaborators of Hongyu Lin 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 Hongyu Lin. Hongyu Lin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 26 | |
| 2 | 2 | |
| 3 | Benchmarking Large Language Models in Retrieval-Augmented Generationbreakdown → | 128 |
| 4 | 6 | |
| 5 | 5 | |
| 6 | 0 | |
| 7 | Unified Structure Generation for Universal Information Extractionbreakdown → | 215 |
| 8 | 10 | |
| 9 | 126 | |
| 10 | 44 | |
| 11 | 22 | |
| 12 | 32 | |
| 13 | 0 | |
| 14 | 16 | |
| 15 | 53 | |
| 16 | 0 | |
| 17 | Predicting price of Taiwan real estates by neural networks and support vector regression | 9 |
| 18 | The prediction of Taiwan 10-year government bond yield | 5 |
| 19 | The prediction of Taiwan government bond yield by neural networks | 1 |
| 20 | 40 |
About Hongyu Lin
Hongyu Lin is a scholar working on Artificial Intelligence, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 56 papers that have together received 1.2k indexed citations. Recurring topics across this work include Topic Modeling (23 papers), Natural Language Processing Techniques (23 papers) and Multimodal Machine Learning Applications (6 papers). The work is most often cited by research in Artificial Intelligence (742 citations), Health Informatics (15 citations) and Management Science and Operations Research (116 citations). Hongyu Lin has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Xianpei Han, Yaojie Lu, Le Sun, Le Sun, B.C. Sheu, Woo‐Hu Tsai, Jiawei Chen, Hua Wu, Le Sun and Xinyan Xiao. Their work appears in journals such as Applied Physics Letters, Optics Letters and IEEE Access.
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.