Dan Garrette

4.1k total citations
23 papers, 507 citations indexed

About

Dan Garrette is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Literature and Literary Theory. According to data from OpenAlex, Dan Garrette has authored 23 papers receiving a total of 507 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 9 papers in Computer Vision and Pattern Recognition and 2 papers in Literature and Literary Theory. Recurrent topics in Dan Garrette's work include Natural Language Processing Techniques (21 papers), Topic Modeling (17 papers) and Multimodal Machine Learning Applications (7 papers). Dan Garrette is often cited by papers focused on Natural Language Processing Techniques (21 papers), Topic Modeling (17 papers) and Multimodal Machine Learning Applications (7 papers). Dan Garrette collaborates with scholars based in United States, Netherlands and Egypt. Dan Garrette's co-authors include Jason Baldridge, Jonathan H. Clark, Eunsol Choi, Michael Collins, Tom Kwiatkowski, Jennimaria Palomaki, Vitaly Nikolaev, Raymond J. Mooney, Katrin Erk and John Wieting and has published in prestigious journals such as Computational Linguistics, Transactions of the Association for Computational Linguistics and Edinburgh Research Explorer (University of Edinburgh).

In The Last Decade

Dan Garrette

20 papers receiving 462 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Dan Garrette United States 11 468 115 41 13 13 23 507
Shijie Wu United States 9 552 1.2× 145 1.3× 30 0.7× 4 0.3× 14 1.1× 12 577
Spandana Gella United States 9 378 0.8× 121 1.1× 54 1.3× 9 0.7× 22 1.7× 25 458
Okan Kolak United States 9 416 0.9× 99 0.9× 74 1.8× 13 1.0× 8 0.6× 11 479
Luís Marujo Portugal 10 502 1.1× 77 0.7× 62 1.5× 7 0.5× 11 0.8× 15 536
Stephan Gouws South Africa 8 449 1.0× 70 0.6× 44 1.1× 4 0.3× 10 0.8× 9 484
Joäo Graça Portugal 12 541 1.2× 85 0.7× 41 1.0× 9 0.7× 10 0.8× 24 579
Ondřej Dušek Czechia 12 396 0.8× 66 0.6× 30 0.7× 6 0.5× 24 1.8× 62 443
Sandipan Dandapat India 12 422 0.9× 72 0.6× 42 1.0× 5 0.4× 16 1.2× 48 464
Markus Dreyer United States 15 523 1.1× 62 0.5× 45 1.1× 8 0.6× 6 0.5× 28 537
Pradeep Dasigi United States 11 527 1.1× 166 1.4× 62 1.5× 11 0.8× 13 1.0× 23 558

Countries citing papers authored by Dan Garrette

Since Specialization
Citations

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

Fields of papers citing papers by Dan Garrette

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dan Garrette

This figure shows the co-authorship network connecting the top 25 collaborators of Dan Garrette. A scholar is included among the top collaborators of Dan Garrette 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 Dan Garrette. Dan Garrette 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.
Shutova, Ekaterina, et al.. (2024). Examining Modularity in Multilingual LMs via Language-Specialized Subnetworks. UvA-DARE (University of Amsterdam). 287–301.
2.
Steenkiste, Sjoerd van, et al.. (2024). The Impact of Depth on Compositional Generalization in Transformer Language Models. 7239–7252.
3.
Garrette, Dan, et al.. (2023). Cross-Lingual Transfer with Language-Specific Subnetworks for Low-Resource Dependency Parsing. Computational Linguistics. 49(3). 613–641.
4.
Liu, Rosanne, Dan Garrette, Chitwan Saharia, et al.. (2023). Character-Aware Models Improve Visual Text Rendering. 16270–16297. 11 indexed citations
5.
Sun, Jiao, Thibault Sellam, Elizabeth A. Clark, et al.. (2023). Dialect-robust Evaluation of Generated Text. 6010–6028. 8 indexed citations
6.
Dozat, Timothy, Xavier García, Dan Garrette, et al.. (2023). FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation. Transactions of the Association for Computational Linguistics. 11. 671–685. 4 indexed citations
7.
Garrette, Dan, et al.. (2023). How do languages influence each other? Studying cross-lingual data sharing during LM fine-tuning. UvA-DARE (University of Amsterdam). 13244–13257. 2 indexed citations
8.
Clark, Jonathan H., Dan Garrette, Iulia Turc, & John Wieting. (2022). Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation. Transactions of the Association for Computational Linguistics. 10. 73–91. 57 indexed citations
9.
Wei, Jason, Dan Garrette, Tal Linzen, & Ellie Pavlick. (2021). Frequency Effects on Syntactic Rule Learning in Transformers. Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing. 932–948. 29 indexed citations
10.
Clark, Jonathan H., Eunsol Choi, Michael Collins, et al.. (2020). TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages. Transactions of the Association for Computational Linguistics. 8. 454–470. 177 indexed citations
11.
12.
Garrette, Dan, et al.. (2016). An Unsupervised Model of Orthographic Variation for Historical Document Transcription. 467–472. 7 indexed citations
13.
Garrette, Dan, et al.. (2015). Unsupervised Code-Switching for Multilingual Historical Document Transcription. 6 indexed citations
14.
Garrette, Dan, Chris Dyer, Jason Baldridge, & Noah A. Smith. (2014). Weakly-Supervised Bayesian Learning of a CCG Supertagger. Figshare. 141–150. 2 indexed citations
15.
Garrette, Dan, Jason D. Mielens, & Jason Baldridge. (2013). Real-World Semi-Supervised Learning of POS-Taggers for Low-Resource Languages. Meeting of the Association for Computational Linguistics. 583–592. 26 indexed citations
16.
Garrette, Dan & Jason Baldridge. (2013). Learning a Part-of-Speech Tagger from Two Hours of Annotation. North American Chapter of the Association for Computational Linguistics. 138–147. 51 indexed citations
17.
Boleda, Gemma, et al.. (2013). Montague Meets Markov: Deep Semantics with Probabilistic Logical Form. Joint Conference on Lexical and Computational Semantics. 1. 11–21. 41 indexed citations
18.
Garrette, Dan & Jason Baldridge. (2012). Type-Supervised Hidden Markov Models for Part-of-Speech Tagging with Incomplete Tag Dictionaries. Empirical Methods in Natural Language Processing. 821–831. 16 indexed citations
19.
Garrette, Dan, Katrin Erk, & Raymond J. Mooney. (2011). Integrating logical representations with probabilistic information using Markov logic. 105–114. 31 indexed citations
20.
Garrette, Dan & Ewan Klein. (2009). Proceedings of the Eighth International Conference on Computational Semantics. 4 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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