Alyssa Mensch
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Information Systems
- Signal Processing
- Computer Networks and Communications
- Co-authors
- Hal DauméAmit GoyalKarl StratosKota YamaguchiJesse DodgeMargaret MitchellXufeng HanTamara L. Berg
- Topics
- Advanced Image and Video Retrieval Techniques (4 papers)Multimodal Machine Learning Applications (3 papers)Topic Modeling (3 papers)
- Journals
- International Journal of Computer VisionConference of the European Chapter of the Association for Computational LinguisticsNational Conference on Artificial Intelligence
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Alyssa Mensch
8 papers receiving 352 citations
Peers
Comparison fields: 5 of 31
- Computer Vision and Pattern Recognition 314
- Artificial Intelligence 193
- Information Systems 22
- Signal Processing 10
- Computer Networks and Communications 9
Countries citing papers authored by Alyssa Mensch
This map shows the geographic impact of Alyssa Mensch'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 Alyssa Mensch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alyssa Mensch more than expected).
Fields of papers citing papers by Alyssa Mensch
This network shows the impact of papers produced by Alyssa Mensch. 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 Alyssa Mensch. The network helps show where Alyssa Mensch may publish in the future.
Co-authorship network of co-authors of Alyssa Mensch
This figure shows the co-authorship network connecting the top 25 collaborators of Alyssa Mensch. A scholar is included among the top collaborators of Alyssa Mensch 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 Alyssa Mensch. Alyssa Mensch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Toward Finding Malicious Cyber Discussions in Social Media. | 3 |
| 3 | A Reverse Approach to Named Entity Extraction and Linking in Microposts. | 9 |
| 4 | Named Entity Recognition in 140 Characters or Less. | 7 |
| 5 | Finding Malicious Cyber Discussions in Social Media | 15 |
| 6 | 54 | |
| 7 | 251 | |
| 8 | Detecting Visual Text | 29 |
About Alyssa Mensch
Alyssa Mensch is a scholar working on Computer Vision and Pattern Recognition, Information Systems and Artificial Intelligence, having authored 8 papers that have together received 369 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (4 papers), Multimodal Machine Learning Applications (3 papers) and Topic Modeling (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (314 citations), Artificial Intelligence (193 citations) and Computational Mathematics (1 citation). Alyssa Mensch has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Hal Daumé, Amit Goyal, Karl Stratos, Kota Yamaguchi, Jesse Dodge, Margaret Mitchell, Xufeng Han, Tamara L. Berg, Yejin Choi and Alexander C. Berg. Their work appears in journals such as International Journal of Computer Vision, Conference of the European Chapter of the Association for Computational Linguistics and National Conference on Artificial Intelligence.
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.