Yelong Shen
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 1%
- Management Science and Operations Research top 5%
- Signal Processing top 10%
- Co-authors
- Jianfeng GaoXiaodong HeLi DengGrégoire MesnilWeizhu ChenRuoming JinXiaodong LiuKevin Duh
- Topics
- Topic Modeling (30 papers)Natural Language Processing Techniques (19 papers)Multimodal Machine Learning Applications (13 papers)
- Journals
- Knowledge and Information SystemsNational University of SingaporearXiv (Cornell University)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Yelong Shen
48 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 103
- Artificial Intelligence 1.4k
- Computer Vision and Pattern Recognition 532
- Information Systems 477
- Management Science and Operations Research 96
- Signal Processing 89
Countries citing papers authored by Yelong Shen
This map shows the geographic impact of Yelong Shen'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 Yelong Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yelong Shen more than expected).
Fields of papers citing papers by Yelong Shen
This network shows the impact of papers produced by Yelong Shen. 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 Yelong Shen. The network helps show where Yelong Shen may publish in the future.
Co-authorship network of co-authors of Yelong Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Yelong Shen. A scholar is included among the top collaborators of Yelong Shen 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 Yelong Shen. Yelong Shen 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 | 1 | |
| 3 | 2 | |
| 4 | 58 | |
| 5 | 2 | |
| 6 | 5 | |
| 7 | 11 | |
| 8 | 11 | |
| 9 | 4 | |
| 10 | 54 | |
| 11 | 17 | |
| 12 | 98 | |
| 13 | 21 | |
| 14 | Adversarial Attacks on Deep Graph Matching | 13 |
| 15 | Multi-Task Learning for Machine Reading Comprehension. | 5 |
| 16 | M-Walk: Learning to Walk in Graph with Monte Carlo Tree Search | 1 |
| 17 | 96 | |
| 18 | Implicit ReasoNet: Modeling Large-Scale Structured Relationships with Shared Memory | 5 |
| 19 | FusionNet: Fusing via Fully-aware Attention with Application to Machine Comprehension | 26 |
| 20 | End-to-end learning of LDA by mirror-descent back propagation over a deep architecture | 11 |
About Yelong Shen
Yelong Shen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Applied Psychology, having authored 50 papers that have together received 1.8k indexed citations. Recurring topics across this work include Topic Modeling (30 papers), Natural Language Processing Techniques (19 papers) and Multimodal Machine Learning Applications (13 papers). The work is most often cited by research in Artificial Intelligence (1.4k citations), Computer Vision and Pattern Recognition (532 citations) and Information Systems (477 citations). Yelong Shen has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Jianfeng Gao, Xiaodong He, Li Deng, Grégoire Mesnil, Weizhu Chen, Ruoming Jin, Xiaodong Liu, Kevin Duh, Po-Sen Huang and Xiaodong Liu. Their work appears in journals such as Knowledge and Information Systems, National University of Singapore 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.