Rachel Rudinger
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Information Systems
- General Social Sciences top 5%
- Sociology and Political Science
- Co-authors
- Benjamin Van DurmeSheng ZhangFrancis FerraroAaron Steven WhiteKevin DuhPushpendre RastogiKyle RawlinsHal Daumé
- Topics
- Topic Modeling (21 papers)Natural Language Processing Techniques (20 papers)Text Readability and Simplification (5 papers)
- Journals
- Transactions of the Association for Computational LinguisticsNPARCarXiv (Cornell University)
- Partner nations
- United StatesIndiaGermany
In The Last Decade
Rachel Rudinger
26 papers receiving 414 citations
Peers
Comparison fields: 5 of 38
- Artificial Intelligence 415
- Computer Vision and Pattern Recognition 64
- Information Systems 25
- General Social Sciences 19
- Sociology and Political Science 19
Countries citing papers authored by Rachel Rudinger
This map shows the geographic impact of Rachel Rudinger'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 Rachel Rudinger with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rachel Rudinger more than expected).
Fields of papers citing papers by Rachel Rudinger
This network shows the impact of papers produced by Rachel Rudinger. 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 Rachel Rudinger. The network helps show where Rachel Rudinger may publish in the future.
Co-authorship network of co-authors of Rachel Rudinger
This figure shows the co-authorship network connecting the top 25 collaborators of Rachel Rudinger. A scholar is included among the top collaborators of Rachel Rudinger 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 Rachel Rudinger. Rachel Rudinger 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 | 0 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 8 | |
| 10 | 4 | |
| 11 | 17 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | 5 | |
| 15 | Towards a Unified Natural Language Inference Framework to Evaluate Sentence Representations | 4 |
| 16 | 13 | |
| 17 | 49 | |
| 18 | 11 | |
| 19 | 59 | |
| 20 | 3 |
About Rachel Rudinger
Rachel Rudinger is a scholar working on Artificial Intelligence, Law and General Social Sciences, having authored 31 papers that have together received 446 indexed citations. Recurring topics across this work include Topic Modeling (21 papers), Natural Language Processing Techniques (20 papers) and Text Readability and Simplification (5 papers). The work is most often cited by research in Artificial Intelligence (415 citations), General Social Sciences (19 citations) and Computer Vision and Pattern Recognition (64 citations). Rachel Rudinger has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Benjamin Van Durme, Sheng Zhang, Francis Ferraro, Aaron Steven White, Kevin Duh, Pushpendre Rastogi, Kyle Rawlins, Hal Daumé, Adam Poliak and J. Edward Hu. Their work appears in journals such as Transactions of the Association for Computational Linguistics, NPARC 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.