Chris Quirk

4.9k citations
75 papers · 2.7k · h-index 24

Impact in

Papers in

Chris Quirk

74 papers receiving 2.4k citations

Peers

Chris Quirk
Comparison fields: 5 of 104
  • Artificial Intelligence 2.4k
  • Computer Vision and Pattern Recognition 355
  • Computer Science Applications 69
  • Information Systems 279
  • Software 43
Replace Kenneth Heafield with:
Kenneth Heafield United Kingdom
Boris Katz United States
Eiichiro Sumita Japan
Kevin Duh United States
Taku Kudo Japan
Palash Goyal United States
Hai Zhao China
Ian Niles United States
Stanley F. Chen United States
Chris Quirk relative to Kenneth Heafield United Kingdom Kenneth Heafield's profile →
Citations per field
00.5×3.5×
Kenneth Heafield · 1×
Citations per year

Countries citing papers authored by Chris Quirk

Since Specialization
Citations

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

Fields of papers citing papers by Chris Quirk

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 75 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2004458
2 2017280
3 2005277
4
Monolingual Machine Translation for Paraphrase Generation
2004209
5 2013169
6
Extracting Parallel Sentences from Comparable Corpora using Document Level Alignment
2010124
7 201592
8 201676
9
A Large Scale Ranker-Based System for Search Query Spelling Correction
201074
10 201557
11
Bayesian Learning of Non-Compositional Phrases with Synchronous Parsing
200849
12
Novel positional encodings to enable tree-based transformers
201945
13 201443
14
Generative models of noisy translations with applications to parallel fragment extraction
200741
15 201840
16 200639
17 202138
18
Learning Phrase-Based Spelling Error Models from Clickthrough Data
201034
19 200932
20 200830

About Chris Quirk

Chris Quirk is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Molecular Biology, Information Systems and Social Psychology, having authored 75 papers that have together received 2.7k indexed citations. Recurring topics across this work include Topic Modeling (65 papers), Natural Language Processing Techniques (64 papers), Text Readability and Simplification (17 papers), Speech and dialogue systems (12 papers), Multimodal Machine Learning Applications (7 papers), Speech Recognition and Synthesis (6 papers), Biomedical Text Mining and Ontologies (6 papers) and Algorithms and Data Compression (4 papers). The work is most often cited by research in Artificial Intelligence (2.4k citations), Computer Vision and Pattern Recognition (355 citations), Computer Science Applications (69 citations), Information Systems (279 citations) and Software (43 citations). Chris Quirk has collaborated with scholars based in United States, United Kingdom and Hong Kong. Frequent co-authors include Chris Brockett, Bill Dolan, Arul Menezes, Kristina Toutanova, Colin Cherry, Michel Galley, Hoifung Poon, Wen-tau Yih, William B. Dolan and Nanyun Peng. Their work appears in journals such as Journal of Hazardous Materials, Bioinformatics, Transactions of the Association for Computational Linguistics, Environmental Science & Technology and Meeting of the Association for 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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