Kevin Gimpel
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 2%
- Molecular Biology
- Sociology and Political Science top 10%
- Co-authors
- Noah A. SmithKaren LivescuMohit BansalBrendan O’ConnorNathan SchneiderDipanjan DasJohn WietingJacob Eisenstein
- Topics
- Natural Language Processing Techniques (66 papers)Topic Modeling (65 papers)Speech Recognition and Synthesis (16 papers)
- Journals
- IEEE Journal of Selected Topics in Signal ProcessingComputational LinguisticsTransactions of the Association for Computational Linguistics
- Partner nations
- United StatesSwitzerlandCanada
In The Last Decade
Kevin Gimpel
74 papers receiving 2.6k citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Artificial Intelligence 2.4k
- Computer Vision and Pattern Recognition 395
- Information Systems 302
- Molecular Biology 158
- Sociology and Political Science 124
Countries citing papers authored by Kevin Gimpel
This map shows the geographic impact of Kevin Gimpel'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 Kevin Gimpel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Gimpel more than expected).
Fields of papers citing papers by Kevin Gimpel
This network shows the impact of papers produced by Kevin Gimpel. 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 Kevin Gimpel. The network helps show where Kevin Gimpel may publish in the future.
Co-authorship network of co-authors of Kevin Gimpel
This figure shows the co-authorship network connecting the top 25 collaborators of Kevin Gimpel. A scholar is included among the top collaborators of Kevin Gimpel 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 Kevin Gimpel. Kevin Gimpel is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 0 | |
| 3 | 10 | |
| 4 | 4 | |
| 5 | 76 | |
| 6 | Learning Approximate Inference Networks for Structured Prediction | 12 |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 1 | |
| 10 | 152 | |
| 11 | 14 | |
| 12 | Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations | 8 |
| 13 | Early Methods for Detecting Adversarial Images | 47 |
| 14 | Joint Modeling of Text and Acoustic-Prosodic Cues for Neural Parsing. | 3 |
| 15 | 83 | |
| 16 | Generalizing and Improving Weight Initialization. | 1 |
| 17 | 179 | |
| 18 | Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, Proceedings, June 9-14, 2013, Westin Peachtree Plaza Hotel, Atlanta, Georgia, USA | 1 |
| 19 | Proceedings of the 49th Annual Meeting of the Association for Computational Linguisticsbreakdown → | 743 |
| 20 | Logistic Normal Priors for Unsupervised Probabilistic Grammar Induction | 45 |
About Kevin Gimpel
Kevin Gimpel is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Communication, having authored 81 papers that have together received 2.8k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (66 papers), Topic Modeling (65 papers) and Speech Recognition and Synthesis (16 papers). The work is most often cited by research in Artificial Intelligence (2.4k citations), Computer Vision and Pattern Recognition (395 citations) and Information Systems (302 citations). Kevin Gimpel has collaborated with scholars based in United States, Switzerland and Canada. Frequent co-authors include Noah A. Smith, Karen Livescu, Mohit Bansal, Brendan O’Connor, Nathan Schneider, Dipanjan Das, John Wieting, Jacob Eisenstein, Michael Heilman and Dani Yogatama. Their work appears in journals such as IEEE Journal of Selected Topics in Signal Processing, Computational Linguistics and Transactions of the Association for Computational Linguistics.
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.