Jesse Dodge

5.3k citations
28 papers · 2.1k · 2 hit papers · h-index 12

Impact in

Papers in

Jesse Dodge

27 papers receiving 2.0k citations

Jesse Dodge's Hit Papers

Green AI 2020 · 752 citations
7520+3+7Years since publication250500750

Peers

Jesse Dodge
Comparison fields: 5 of 128
  • Artificial Intelligence 1.2k
  • Health Informatics 44
  • Computer Vision and Pattern Recognition 573
  • Computer Science Applications 65
  • Safety Research 92
Replace Peter R. Lewis with:
Peter R. Lewis United Kingdom
Maarten van Someren Netherlands
Weizhe Yuan United States
Norisma Idris Malaysia
Wei Ye China
Linyi Yang China
Zhengbao Jiang United States
Cunxiang Wang China
Johannes Schneider Switzerland
Jesse Dodge relative to Peter R. Lewis United Kingdom Peter R. Lewis's profile →
Citations per field
00.5×6.8×
Peter R. Lewis · 1×
Citations per year

Countries citing papers authored by Jesse Dodge

Since Specialization
Citations

This map shows the geographic impact of Jesse Dodge'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 Dodge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jesse Dodge more than expected).

Fields of papers citing papers by Jesse Dodge

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jesse Dodge. 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 Dodge. The network helps show where Jesse Dodge may publish in the future.

Co-authors

The 25 scholars most cited alongside Jesse Dodge, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jesse Dodge Line = papers co-authored together Jesse Dodge links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Green AI
Hit paper breakdown →
2020752
2
Retrofitting Word Vectors to Semantic Lexicons
Hit paper breakdown →
2015483
3 2012279
4 2022126
5 2019115
6 201560
7 202149
8 201449
9
Detecting Visual Text
201229
10 202224
11 202216
12 202313
13 202310
14 20248
15 20258
16 20148
17 20237
18 20233
19 20213
20 20232

About Jesse Dodge

Jesse Dodge is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Safety Research, General Social Sciences and Statistics, Probability and Uncertainty, having authored 28 papers that have together received 2.1k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (14 papers), Topic Modeling (13 papers), Advanced Image and Video Retrieval Techniques (4 papers), Multimodal Machine Learning Applications (3 papers), Speech and dialogue systems (2 papers), Ethics and Social Impacts of AI (2 papers), Computational and Text Analysis Methods (2 papers) and Speech Recognition and Synthesis (2 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Health Informatics (44 citations), Computer Vision and Pattern Recognition (573 citations), Computer Science Applications (65 citations) and Safety Research (92 citations). Jesse Dodge has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Noah A. Smith, Roy Schwartz, Oren Etzioni, Eduard Hovy, Chris Dyer, Manaal Faruqui, Sunil Kumar Jauhar, Margaret Mitchell, Kota Yamaguchi and Amit Goyal. Their work appears in journals such as International Journal of Computer Vision, Communications of the ACM, Nature Machine Intelligence, Mosquito news and UNC Libraries.

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.

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