Trevor Cohn

7.9k citations
187 papers · 3.9k · h-index 33

Impact in

Papers in

    • Topic Modeling 121
    • Natural Language Processing Techniques 114
    • Speech Recognition and Synthesis 23
    • Advanced Text Analysis Techniques 19
    • Speech and dialogue systems 15
    • Text Readability and Simplification 12
    • Algorithms and Data Compression 11
    • Multimodal Machine Learning Applications 17

Trevor Cohn

176 papers receiving 3.6k citations

Peers

Trevor Cohn
Comparison fields: 5 of 129
  • Artificial Intelligence 3.2k
  • Computer Vision and Pattern Recognition 575
  • Transportation 150
  • Information Systems 371
  • Statistical and Nonlinear Physics 202
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Citations per field
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Citations per year

Countries citing papers authored by Trevor Cohn

Since Specialization
Citations

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

Fields of papers citing papers by Trevor Cohn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Trevor Cohn, 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 Trevor Cohn Line = papers co-authored together Trevor Cohn links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 187 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015221
2 2018212
3 2017148
4 2018124
5
QuEst - A translation quality estimation framework
2013113
6 2008104
7 201794
8 201688
9 201888
10 201384
11
A Discriminative Latent Variable Model for Statistical Machine Translation
200883
12 201681
13
Machine Translation by Triangulation: Making Effective Use of Multi-Parallel Corpora
200778
14 200675
15
Modelling Annotator Bias with Multi-task Gaussian Processes: An Application to Machine Translation Quality Estimation
201375
16 200972
17 201369
18 200865
19 201763
20 200661

About Trevor Cohn

Trevor Cohn is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Molecular Biology and Information Systems, having authored 187 papers that have together received 3.9k indexed citations. Recurring topics across this work include Topic Modeling (121 papers), Natural Language Processing Techniques (114 papers), Speech Recognition and Synthesis (23 papers), Advanced Text Analysis Techniques (19 papers), Multimodal Machine Learning Applications (17 papers), Speech and dialogue systems (15 papers), Text Readability and Simplification (12 papers) and Algorithms and Data Compression (11 papers). The work is most often cited by research in Artificial Intelligence (3.2k citations), Computer Vision and Pattern Recognition (575 citations), Transportation (150 citations), Information Systems (371 citations) and Statistical and Nonlinear Physics (202 citations). Trevor Cohn has collaborated with scholars based in Australia, United Kingdom and United States. Frequent co-authors include Mirella Lapata, Gholamreza Haffari, Steven Bird, Phil Blunsom, Phil Blunsom, Long Duong, Timothy Baldwin, Daniel Beck, Lucia Specia and Daniel Preoțiuc-Pietro. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Language Resources and Evaluation, Schizophrenia Research, ACM Transactions on Information Systems and Computational Linguistics.

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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