Jesse Dodge

4.8k total citations · 2 hit papers
27 papers, 1.8k citations indexed

About

Jesse Dodge is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Safety Research. According to data from OpenAlex, Jesse Dodge has authored 27 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 2 papers in Safety Research. Recurrent topics in Jesse Dodge's work include Natural Language Processing Techniques (14 papers), Topic Modeling (13 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Jesse Dodge is often cited by papers focused on Natural Language Processing Techniques (14 papers), Topic Modeling (13 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Jesse Dodge collaborates with scholars based in United States, Canada and United Kingdom. Jesse Dodge's co-authors include Noah A. Smith, Roy Schwartz, Oren Etzioni, Chris Dyer, Eduard Hovy, Sunil Kumar Jauhar, Manaal Faruqui, Margaret Mitchell, Alyssa Mensch and Karl Stratos and has published in prestigious journals such as Communications of the ACM, International Journal of Computer Vision and Nature Machine Intelligence.

In The Last Decade

Jesse Dodge

26 papers receiving 1.7k citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Green AI

2020 604 citations Roy Schwartz, Jesse Dodge et al. profile →
Retrofitting Word Vectors to Semantic Lexicons

2015 426 citations Manaal Faruqui, Jesse Dodge et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Jesse Dodge	1.1k	515	159	133	108	27	1.8k
Norisma Idris	1.6k 1.4×	194 0.4×	92 0.6×	287 2.2×	77 0.7×	77	2.1k
Weizhe Yuan	1.4k 1.3×	411 0.8×	46 0.3×	344 2.6×	122 1.1×	13	2.1k
Jinlan Fu	2.1k 1.9×	538 1.0×	136 0.9×	439 3.3×	124 1.1×	28	2.9k
Stefano V. Albrecht	691 0.6×	214 0.4×	47 0.3×	120 0.9×	112 1.0×	37	1.2k
Ming Zhou	1.5k 1.4×	436 0.8×	127 0.8×	195 1.5×	88 0.8×	118	2.0k
Sungchul Kim	943 0.9×	304 0.6×	47 0.3×	237 1.8×	92 0.9×	93	1.4k
Zhengbao Jiang	1.8k 1.6×	508 1.0×	50 0.3×	485 3.6×	138 1.3×	16	2.6k
Tong Xu	1.2k 1.1×	527 1.0×	76 0.5×	468 3.5×	113 1.0×	149	2.2k
Maarten van Someren	620 0.6×	149 0.3×	50 0.3×	244 1.8×	65 0.6×	43	1.2k

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-authorship network of co-authors of Jesse Dodge

This figure shows the co-authorship network connecting the top 25 collaborators of Jesse Dodge. A scholar is included among the top collaborators of Jesse Dodge 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 Jesse Dodge. Jesse Dodge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Gu, Yuling, et al.. (2025). OLMES: A Standard for Language Model Evaluations. 5005–5033. 1 indexed citations

Jiang, Liwei, Jena D. Hwang, Chandra Bhagavatula, et al.. (2025). Investigating machine moral judgement through the Delphi experiment. Nature Machine Intelligence. 7(1). 145–160. 5 indexed citations

Guan, Jian, Jesse Dodge, David Wadden, Minlie Huang, & Hao Peng. (2024). Language Models Hallucinate, but May Excel at Fact Verification. 1090–1111. 3 indexed citations

Strubell, Emma, et al.. (2024). Scalable Data Ablation Approximations for Language Models through Modular Training and Merging. 21125–21141.

Lucy, Li, Suchin Gururangan, Luca Soldaini, et al.. (2024). AboutMe: Using Self-Descriptions in Webpages to Document the Effects of English Pretraining Data Filters. 7393–7420. 1 indexed citations

Subramani, Nishant, Alexandra Sasha Luccioni, Jesse Dodge, & Margaret Mitchell. (2023). Detecting Personal Information in Training Corpora: an Analysis. 208–220. 8 indexed citations

Serrano, Sofia, Jesse Dodge, & Noah A. Smith. (2023). Stubborn Lexical Bias in Data and Models. 8131–8146. 3 indexed citations

Peters, Matthew E., et al.. (2023). AdapterSoup: Weight Averaging to Improve Generalization of Pretrained Language Models. Open access LMU (Ludwid Maxmilian's Universitat Munchen). 2054–2063. 10 indexed citations

Smith, Noah A., et al.. (2023). Reproducibility in NLP: What Have We Learned from the Checklist?. 12789–12811. 1 indexed citations

10.

Lucy, Li, Jesse Dodge, David Bamman, & Katherine A. Keith. (2023). Words as Gatekeepers: Measuring Discipline-specific Terms and Meanings in Scholarly Publications. 6929–6947. 2 indexed citations

11.

Sinha, Koustuv, et al.. (2023). ML Reproducibility Challenge 2022. Zenodo (CERN European Organization for Nuclear Research). 7 indexed citations

12.

Gardner, Matt, William Merrill, Jesse Dodge, et al.. (2021). Competency Problems: On Finding and Removing Artifacts in Language Data. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 1801–1813. 46 indexed citations

13.

Sinha, Koustuv, et al.. (2021). ML Reproducibility Challenge 2020. Zenodo (CERN European Organization for Nuclear Research). 3 indexed citations

14.

Dodge, Jesse, Suchin Gururangan, Dallas Card, Roy Schwartz, & Noah A. Smith. (2019). Show Your Work: Improved Reporting of Experimental Results. 2185–2194. 105 indexed citations

15.

Dodge, Jesse, Roy Schwartz, Hao Peng, & Noah A. Smith. (2019). RNN Architecture Learning with Sparse Regularization. 1179–1184. 2 indexed citations

16.

Faruqui, Manaal, Jesse Dodge, Sunil Kumar Jauhar, et al.. (2015). Retrofitting Word Vectors to Semantic Lexicons. 1606–1615. 426 indexed citations breakdown →

17.

Thomson, Sam, Brendan O’Connor, Jeffrey Flanigan, et al.. (2014). CMU: Arc-Factored, Discriminative Semantic Dependency Parsing. Figshare. 176–180. 8 indexed citations

18.

Lee, Kenton, Yoav Artzi, Jesse Dodge, & Luke Zettlemoyer. (2014). Context-dependent Semantic Parsing for Time Expressions. 1437–1447. 43 indexed citations

19.

Mitchell, Margaret, Jesse Dodge, Amit Goyal, et al.. (2012). Midge: Generating Image Descriptions From Computer Vision Detections. Conference of the European Chapter of the Association for Computational Linguistics. 8(2). 747–756. 251 indexed citations

20.

Dodge, Jesse, Amit Goyal, Xufeng Han, et al.. (2012). Detecting Visual Text. 762–772. 29 indexed citations

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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