Shuohang Wang
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 5%
- Biomedical Engineering
- Molecular Biology
- Topics
- Topic Modeling (31 papers)Natural Language Processing Techniques (24 papers)Multimodal Machine Learning Applications (21 papers)
- Journals
- Chemical Engineering JournalJournal of Geotechnical and Geoenvironmental EngineeringIEEE/ACM Transactions on Audio Speech and Language Processing
- Partner nations
- United StatesSingaporeChina
In The Last Decade
Shuohang Wang
39 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 115
- Artificial Intelligence 1.2k
- Computer Vision and Pattern Recognition 585
- Information Systems 153
- Biomedical Engineering 54
- Molecular Biology 48
Countries citing papers authored by Shuohang Wang
This map shows the geographic impact of Shuohang Wang'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 Shuohang Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuohang Wang more than expected).
Fields of papers citing papers by Shuohang Wang
This network shows the impact of papers produced by Shuohang Wang. 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 Shuohang Wang. The network helps show where Shuohang Wang may publish in the future.
Co-authorship network of co-authors of Shuohang Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Shuohang Wang. A scholar is included among the top collaborators of Shuohang Wang 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 Shuohang Wang. Shuohang Wang 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 | 2 | |
| 3 | 18 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 20 | |
| 7 | 31 | |
| 8 | 2 | |
| 9 | An Empirical Study of Training End-to-End Vision-and-Language Transformersbreakdown → | 204 |
| 10 | 26 | |
| 11 | 53 | |
| 12 | 89 | |
| 13 | 9 | |
| 14 | 41 | |
| 15 | 32 | |
| 16 | Compositional De-Attention Networks | 9 |
| 17 | 28 | |
| 18 | R 3 : Reinforced Ranker-Reader for Open-Domain Question Answering. | 88 |
| 19 | Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering | 49 |
| 20 | Machine Comprehension Using Match-LSTM and Answer Pointer | 58 |
About Shuohang Wang
Shuohang Wang is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Biochemistry, having authored 41 papers that have together received 1.5k indexed citations. Recurring topics across this work include Topic Modeling (31 papers), Natural Language Processing Techniques (24 papers) and Multimodal Machine Learning Applications (21 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Computer Vision and Pattern Recognition (585 citations) and Health Informatics (23 citations). Shuohang Wang has collaborated with scholars based in United States, Singapore and China. Frequent co-authors include Jing Jiang, Zhe Gan, Yang Liu, Ruochen Xu, Chenguang Zhu, Xu Yi‐chong, Yuwei Fang, Siqi Sun, Dan Iter and Michael Zeng. Their work appears in journals such as Chemical Engineering Journal, Journal of Geotechnical and Geoenvironmental Engineering and IEEE/ACM Transactions on Audio Speech and Language Processing.
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.