Jonathan May

2.8k total citations
77 papers, 1.2k citations indexed

About

Jonathan May is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Jonathan May has authored 77 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Artificial Intelligence, 14 papers in Computer Vision and Pattern Recognition and 5 papers in Computational Theory and Mathematics. Recurrent topics in Jonathan May's work include Topic Modeling (55 papers), Natural Language Processing Techniques (54 papers) and Multimodal Machine Learning Applications (11 papers). Jonathan May is often cited by papers focused on Topic Modeling (55 papers), Natural Language Processing Techniques (54 papers) and Multimodal Machine Learning Applications (11 papers). Jonathan May collaborates with scholars based in United States, Spain and Germany. Jonathan May's co-authors include Kevin Knight, Mark Hopkins, Heng Ji, Xiaoman Pan, Boliang Zhang, Joel Nothman, Xiang Ren, Mozhdeh Gheini, Nanyun Peng and Marjan Ghazvininejad and has published in prestigious journals such as Biotechnology and Bioengineering, Theoretical Computer Science and Computational Linguistics.

In The Last Decade

Jonathan May

69 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jonathan May United States 19 1.1k 218 89 55 52 77 1.2k
Diarmuid Ó Séaghdha United Kingdom 18 915 0.8× 123 0.6× 229 2.6× 134 2.4× 20 0.4× 32 1.2k
Marina Danilevsky United States 13 547 0.5× 75 0.3× 143 1.6× 38 0.7× 16 0.3× 38 722
Shih-Hung Wu Taiwan 16 687 0.6× 107 0.5× 178 2.0× 101 1.8× 24 0.5× 87 865
Lizhen Liu China 15 482 0.4× 86 0.4× 174 2.0× 22 0.4× 15 0.3× 102 663
Nanda Kambhatla United States 12 792 0.7× 76 0.3× 151 1.7× 99 1.8× 18 0.3× 25 902
John Tait United Kingdom 14 455 0.4× 171 0.8× 188 2.1× 41 0.7× 21 0.4× 65 692
Weihua Peng China 9 484 0.4× 52 0.2× 109 1.2× 86 1.6× 17 0.3× 29 722
Hiroya Takamura Japan 17 1.1k 1.0× 135 0.6× 175 2.0× 32 0.6× 16 0.3× 131 1.2k
Jungyun Seo South Korea 15 922 0.8× 86 0.4× 323 3.6× 45 0.8× 20 0.4× 118 1.1k
Xinyan Xiao China 17 1.1k 1.0× 346 1.6× 125 1.4× 68 1.2× 7 0.1× 46 1.3k

Countries citing papers authored by Jonathan May

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan May

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan May

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

All Works

20 of 20 papers shown
1.
Lee, Dong‐Ho, Woojeong Jin, Minwoo Kim, et al.. (2023). Analyzing Norm Violations in Live-Stream Chat. 852–868.
4.
Ren, Xiang, et al.. (2023). Cross-lingual Continual Learning. 3908–3943. 3 indexed citations
5.
Sankar, Chinnadhurai, Christopher Lin, Kaushik Ram Sadagopan, et al.. (2022). Know Thy Strengths: Comprehensive Dialogue State Tracking Diagnostics. 5345–5359. 1 indexed citations
6.
Gheini, Mozhdeh, Xiang Ren, & Jonathan May. (2021). On the Strengths of Cross-Attention in Pretrained Transformers for Machine Translation.. arXiv (Cornell University). 1 indexed citations
7.
Li, Manling, Qi Zeng, Ying Lin, et al.. (2020). Connecting the Dots: Event Graph Schema Induction with Path Language Modeling. 684–695. 44 indexed citations
8.
Lu, Di, Heng Ji, Jonathan May, et al.. (2020). Cross-lingual Structure Transfer for Zero-resource Event Extraction. Language Resources and Evaluation. 1976–1981. 5 indexed citations
9.
May, Jonathan, et al.. (2019). Comprehensible Context-driven Text Game Playing. 70. 1–8. 9 indexed citations
10.
Freedman, Marjorie, et al.. (2019). Contextualized Cross-Lingual Event Trigger Extraction with Minimal Resources. 656–665. 19 indexed citations
11.
Pan, Xiaoman, Boliang Zhang, Jonathan May, et al.. (2017). Cross-lingual Name Tagging and Linking for 282 Languages. 1946–1958. 202 indexed citations
12.
Huang, Lifu, Jonathan May, Xiaoman Pan, et al.. (2017). Liberal Entity Extraction: Rapid Construction of Fine-Grained Entity Typing Systems. Big Data. 5(1). 19–31. 11 indexed citations
13.
Choi, Eunsol, et al.. (2016). Extracting Structured Scholarly Information from the Machine Translation Literature. Language Resources and Evaluation. 421–425. 3 indexed citations
14.
May, Jonathan, et al.. (2014). An Arabizi-English social media statistical machine translation system.. Conference of the Association for Machine Translation in the Americas. 329–341. 10 indexed citations
15.
Hopkins, Mark & Jonathan May. (2013). Models of Translation Competitions. Meeting of the Association for Computational Linguistics. 1416–1424. 11 indexed citations
16.
Pighin, Daniele, Lluı́s Màrquez, & Jonathan May. (2012). An Analysis (and an Annotated Corpus) of User Responses to Machine Translation Output. Language Resources and Evaluation. 1131–1136. 4 indexed citations
17.
May, Jonathan, Kevin Knight, & Heiko Vogler. (2010). Efficient Inference through Cascades of Weighted Tree Transducers. Meeting of the Association for Computational Linguistics. 1058–1066. 7 indexed citations
18.
Maletti, Andreas, et al.. (2009). Backward and forward bisimulation minimization of tree automata. Theoretical Computer Science. 410(37). 3539–3552. 20 indexed citations
19.
May, Jonathan & Kevin Knight. (2007). Syntactic Re-Alignment Models for Machine Translation. Empirical Methods in Natural Language Processing. 360–368. 28 indexed citations
20.
Xu, Jinxi, et al.. (2002). TREC 2002 QA at BBN: Answer Selection and Confidence Estimation.. Text REtrieval Conference. 28 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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