Jesse Vig
Impact in
- Information Systems top 1%
- Recommender Systems and Techniques
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Advanced Graph Neural Networks
- Explainable Artificial Intelligence (XAI)
- Advanced Text Analysis Techniques
Papers in ⓘ
-
- Natural Language Processing Techniques 10
- Topic Modeling 9
- Advanced Text Analysis Techniques 4
- Speech and dialogue systems 2
-
- Recommender Systems and Techniques 7
- Co-authors
- John Riedl (6 shared papers)Shilad Sen (6 shared papers)Nora Plesofsky-Vig (1 shared paper)Robert Brambl (1 shared paper)Nazneen Fatema Rajani (3 shared papers)Anamaria Crisan (1 shared paper)Margaret Drouhard (1 shared paper)Stuart M. Shieber (1 shared paper)
- Journals
- ACM Transactions on Interactive Intelligent Systems (1 paper)Journal of Molecular Evolution (1 paper)arXiv (Cornell University) (2 papers)Neural Information Processing Systems (1 paper)
- Partner nations
- United States
In The Last Decade
Jesse Vig
18 papers receiving 754 citations
Peers
Comparison fields: 5 of 71
- Information Systems 461
- Artificial Intelligence 455
- Health Informatics 19
- Computer Vision and Pattern Recognition 186
- Computational Mathematics 5
Countries citing papers authored by Jesse Vig
This map shows the geographic impact of Jesse Vig'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 Jesse Vig with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jesse Vig more than expected).
Fields of papers citing papers by Jesse Vig
This network shows the impact of papers produced by Jesse Vig. 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 Jesse Vig. The network helps show where Jesse Vig may publish in the future.
Co-authors
The 25 scholars most cited alongside Jesse Vig, 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 | 2009 | 206 | |
| 2 | 2009 | 185 | |
| 3 | Investigating Gender Bias in Language Models Using Causal Mediation Analysis | 2020 | 84 |
| 4 | 2012 | 83 | |
| 5 | 1992 | 65 | |
| 6 | 2022 | 52 | |
| 7 | 2011 | 30 | |
| 8 | 2009 | 23 | |
| 9 | 2022 | 19 | |
| 10 | 2010 | 12 | |
| 11 | Visualizing Attention in Transformer-Based Language models | 2019 | 8 |
| 12 | 2022 | 7 | |
| 13 | 2023 | 7 | |
| 14 | 2024 | 6 | |
| 15 | 2023 | 5 | |
| 16 | 2023 | 5 | |
| 17 | 2010 | 1 | |
| 18 | 2021 | 1 | |
| 19 | 2025 | 0 |
About Jesse Vig
Jesse Vig is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Communication and Molecular Biology, having authored 19 papers that have together received 799 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (10 papers), Topic Modeling (9 papers), Recommender Systems and Techniques (7 papers), Video Analysis and Summarization (6 papers), Advanced Text Analysis Techniques (4 papers), Image Retrieval and Classification Techniques (2 papers), Speech and dialogue systems (2 papers) and Wikis in Education and Collaboration (2 papers). The work is most often cited by research in Information Systems (461 citations), Artificial Intelligence (455 citations), Health Informatics (19 citations), Computer Vision and Pattern Recognition (186 citations) and Computational Mathematics (5 citations). Jesse Vig has collaborated with scholars based in United States. Frequent co-authors include John Riedl, Shilad Sen, Nora Plesofsky-Vig, Robert Brambl, Nazneen Fatema Rajani, Anamaria Crisan, Margaret Drouhard, Stuart M. Shieber, Yaron Singer and Sebastian Gehrmann. Their work appears in journals such as ACM Transactions on Interactive Intelligent Systems, Journal of Molecular Evolution, arXiv (Cornell University) and Neural Information Processing Systems.
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.