Ledell Wu
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Advanced Graph Neural Networks
-
- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Advanced Neural Network Applications
Papers in
-
- Topic Modeling 8
- Natural Language Processing Techniques 7
- Text and Document Classification Technologies 1
-
- Advanced Image and Video Retrieval Techniques 2
- Multimodal Machine Learning Applications 2
- Co-authors
- Luke Zettlemoyer (2 shared papers)Fabio Petroni (2 shared papers)Sebastian Riedel (2 shared papers)Martin Josifoski (1 shared paper)Binhui Xie (1 shared paper)Xinlong Wang (1 shared paper)Tiejun Huang (1 shared paper)Yuxin Fang (1 shared paper)
- Journals
- Transactions of the Association for Computational Linguistics (1 paper)IEEE Transactions on Knowledge and Data Engineering (1 paper)ACM Transactions on Information Systems (1 paper)Machine Intelligence Research (1 paper)arXiv (Cornell University) (2 papers)
- Partner nations
- ChinaIsraelUnited Kingdom
In The Last Decade
Ledell Wu
11 papers receiving 836 citations
Ledell Wu's Hit Papers
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 584
- Computer Vision and Pattern Recognition 326
- Health Informatics 7
- Management Science and Operations Research 61
- Information Systems 76
Countries citing papers authored by Ledell Wu
This map shows the geographic impact of Ledell Wu'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 Ledell Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ledell Wu more than expected).
Fields of papers citing papers by Ledell Wu
This network shows the impact of papers produced by Ledell Wu. 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 Ledell Wu. The network helps show where Ledell Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ledell Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | EVA: Exploring the Limits of Masked Visual Representation Learning at Scale Hit paper breakdown → | 2023 | 363 |
| 2 | Scalable Zero-shot Entity Linking with Dense Entity Retrieval Hit paper breakdown → | 2020 | 240 |
| 3 | 2018 | 97 | |
| 4 | 2022 | 62 | |
| 5 | 2020 | 51 | |
| 6 | 2023 | 28 | |
| 7 | 2024 | 17 | |
| 8 | 2023 | 14 | |
| 9 | 2023 | 4 | |
| 10 | 2024 | 4 | |
| 11 | 2020 | 4 |
About Ledell Wu
Ledell Wu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research, Information Systems and Insect Science, having authored 11 papers that have together received 884 indexed citations. Recurring topics across this work include Topic Modeling (8 papers), Natural Language Processing Techniques (7 papers), Advanced Image and Video Retrieval Techniques (2 papers), Multimodal Machine Learning Applications (2 papers), Data Quality and Management (2 papers), Web Data Mining and Analysis (1 paper), Information Retrieval and Search Behavior (1 paper) and Text and Document Classification Technologies (1 paper). The work is most often cited by research in Artificial Intelligence (584 citations), Computer Vision and Pattern Recognition (326 citations), Health Informatics (7 citations), Management Science and Operations Research (61 citations) and Information Systems (76 citations). Ledell Wu has collaborated with scholars based in China, Israel and United Kingdom. Frequent co-authors include Luke Zettlemoyer, Fabio Petroni, Sebastian Riedel, Martin Josifoski, Binhui Xie, Xinlong Wang, Tiejun Huang, Yuxin Fang, Quan Sun and Yue Cao. Their work appears in journals such as Transactions of the Association for Computational Linguistics, IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Information Systems, Machine Intelligence Research 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.