Hung-yi Lee
- Artificial Intelligence top 0.2%
- Signal Processing top 0.2%
- Computer Vision and Pattern Recognition top 2%
- Electrical and Electronic Engineering
- Management Science and Operations Research top 2%
- Co-authors
- Fan-Keng SunLin-shan LeeShang-Wen LiAndy T. LiuJu-Chieh ChouHaibin WuShu-Wen YangShinji Watanabe
- Topics
- Speech Recognition and Synthesis (151 papers)Natural Language Processing Techniques (106 papers)Topic Modeling (98 papers)
- Partner nations
- TaiwanUnited StatesHong Kong
In The Last Decade
Hung-yi Lee
232 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 147
- Artificial Intelligence 3.5k
- Signal Processing 2.0k
- Computer Vision and Pattern Recognition 617
- Electrical and Electronic Engineering 251
- Management Science and Operations Research 219
Countries citing papers authored by Hung-yi Lee
This map shows the geographic impact of Hung-yi 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 Hung-yi Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hung-yi Lee more than expected).
Fields of papers citing papers by Hung-yi Lee
This network shows the impact of papers produced by Hung-yi 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 Hung-yi Lee. The network helps show where Hung-yi Lee may publish in the future.
Co-authorship network of co-authors of Hung-yi Lee
This figure shows the co-authorship network connecting the top 25 collaborators of Hung-yi Lee. A scholar is included among the top collaborators of Hung-yi 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 Hung-yi Lee. Hung-yi Lee is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 4 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 0 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 2 | |
| 13 | 19 | |
| 14 | 16 | |
| 15 | 26 | |
| 16 | 58 | |
| 17 | TaylorGAN: Neighbor-Augmented Policy Update Towards Sample-Efficient Natural Language Generation | 1 |
| 18 | Further Boosting BERT-based Models by Duplicating Existing Layers: Some Intriguing Phenomena inside BERT | 1 |
| 19 | LAMAL: LAnguage Modeling Is All You Need for Lifelong Language Learning | 8 |
| 20 | Unsupervised Learning of Audio Segment Representations using Sequence-to-sequence Recurrent Neural Networks | 13 |
About Hung-yi Lee
Hung-yi Lee is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 259 papers that have together received 4.6k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (151 papers), Natural Language Processing Techniques (106 papers) and Topic Modeling (98 papers). The work is most often cited by research in Signal Processing (2.0k citations), Artificial Intelligence (3.5k citations) and Computer Vision and Pattern Recognition (617 citations). Hung-yi Lee has collaborated with scholars based in Taiwan, United States and Hong Kong. Frequent co-authors include Fan-Keng Sun, Lin-shan Lee, Shang-Wen Li, Andy T. Liu, Ju-Chieh Chou, Haibin Wu, Shu-Wen Yang, Shinji Watanabe, Yung-Sung Chuang and Yun-Nung Chen. Their work appears in journals such as Plastic & Reconstructive Surgery, Machine Learning and Annals of Surgical Oncology.
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.