John Hewitt
Impact in
- Artificial Intelligence top 2%
- Topic Modeling
- Natural Language Processing Techniques
- Text Readability and Simplification
- Speech and dialogue systems
- Explainable Artificial Intelligence (XAI)
- Health Informatics top 5%
Papers in
-
- Natural Language Processing Techniques 9
- Topic Modeling 9
- Speech and dialogue systems 3
- Adversarial Robustness in Machine Learning 1
-
- Historical Geography and Cartography 1
- Co-authors
- Christopher D. ManningPercy LiangNelson F. LiuFabio PetroniKevin LinAshwin ParanjapeMichele BevilacquaUrvashi Khandelwal
- Journals
- Transactions of the Association for Computational Linguistics (1 paper)Proceedings of the National Academy of Sciences (1 paper)Monash University Research Portal (Monash University) (1 paper)arXiv (Cornell University) (1 paper)Conference of the Association for Machine Translation in the Americas (1 paper)
- Partner nations
- United StatesFranceGermany
In The Last Decade
John Hewitt
10 papers receiving 908 citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Artificial Intelligence 771
- Health Informatics 30
- Computer Vision and Pattern Recognition 183
- General Social Sciences 19
- Software 22
Countries citing papers authored by John Hewitt
This map shows the geographic impact of John Hewitt'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 John Hewitt with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Hewitt more than expected).
Fields of papers citing papers by John Hewitt
This network shows the impact of papers produced by John Hewitt. 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 John Hewitt. The network helps show where John Hewitt may publish in the future.
Co-authors
The 25 scholars most cited alongside John Hewitt, 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 | Lost in the Middle: How Language Models Use Long Contexts Hit paper breakdown → | 2024 | 285 |
| 2 | 2021 | 15 | |
| 3 | 2020 | 157 | |
| 4 | Hit paper breakdown → | 2019 | 286 |
| 5 | 2019 | 181 | |
| 6 | XNMT: the eXtensible Neural Machine Translation toolkit | 2018 | 13 |
| 7 | 2018 | 7 | |
| 8 | 2018 | 19 | |
| 9 | 2017 | 10 | |
| 10 | Automatic Construction of Morphologically Motivated Translation Models for Highly Inflected, Low-Resource Languages. | 2016 | 2 |
| 11 | The Terrestrial Sphere of 'The Spheres' Tapestries | 2010 | 0 |
About John Hewitt
John Hewitt is a scholar working on Artificial Intelligence, Geography, Planning and Development, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Infectious Diseases, having authored 11 papers that have together received 975 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (9 papers), Topic Modeling (9 papers), Speech and dialogue systems (3 papers), Multimodal Machine Learning Applications (3 papers), Advanced Image and Video Retrieval Techniques (1 paper), Ferroelectric and Negative Capacitance Devices (1 paper), Historical Geography and Cartography (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Artificial Intelligence (771 citations), Health Informatics (30 citations), Computer Vision and Pattern Recognition (183 citations), General Social Sciences (19 citations) and Software (22 citations). John Hewitt has collaborated with scholars based in United States, France and Germany. Frequent co-authors include Christopher D. Manning, Percy Liang, Nelson F. Liu, Fabio Petroni, Kevin Lin, Ashwin Paranjape, Michele Bevilacqua, Urvashi Khandelwal, Kevin B. Clark and Omer Levy. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Proceedings of the National Academy of Sciences, Monash University Research Portal (Monash University), arXiv (Cornell University) and Conference of the Association for Machine Translation in the Americas.
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.