Countries citing papers authored by Marine Carpuat
Since
Specialization
Citations
This map shows the geographic impact of Marine Carpuat'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 Marine Carpuat with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marine Carpuat more than expected).
This network shows the impact of papers produced by Marine Carpuat. 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 Marine Carpuat. The network helps show where Marine Carpuat may publish in the future.
Co-authorship network of co-authors of Marine Carpuat
This figure shows the co-authorship network connecting the top 25 collaborators of Marine Carpuat.
A scholar is included among the top collaborators of Marine Carpuat 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 Marine Carpuat. Marine Carpuat is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Axelrod, Amittai, Yogarshi Vyas, Marianna J. Martindale, & Marine Carpuat. (2015). Class-based N-gram language difference models for data selection.. IWSLT.7 indexed citations
10.
Carpuat, Marine. (2013). NRC: A Machine Translation Approach to Cross-Lingual Word Sense Disambiguation (SemEval-2013 Task 10). Joint Conference on Lexical and Computational Semantics. 188–192.9 indexed citations
11.
Goutte, Cyril, Serge Léger, & Marine Carpuat. (2013). Feature Space Selection and Combination for Native Language Identification. NPARC. 96–100.10 indexed citations
12.
Fujita, Atsushi & Marine Carpuat. (2013). FUN-NRC: Paraphrase-augmented Phrase-based SMT Systems for NTCIR-10 PatentMT. NTCIR.1 indexed citations
13.
Goutte, Cyril, Marine Carpuat, & George Foster. (2012). The Impact of Sentence Alignment Errors on Phrase-Based Machine Translation Performance. NPARC.18 indexed citations
14.
Carpuat, Marine & Dekai Wu. (2008). Evaluation of Context-Dependent Phrasal Translation Lexicons for Statistical Machine Translation. Language Resources and Evaluation.10 indexed citations
15.
Yu, Xiaofeng, Marine Carpuat, & Dekai Wu. (2006). Boosting for Chinese Named Entity Recognition. Meeting of the Association for Computational Linguistics. 150–153.6 indexed citations
16.
Carpuat, Marine & Dekai Wu. (2005). Evaluating the Word Sense Disambiguation Performance of Statistical Machine Translation. International Joint Conference on Natural Language Processing.18 indexed citations
17.
Carpuat, Marine, Weifeng Su, & Dekai Wu. (2004). Augmenting Ensemble Classification for Word Sense Disambiguation with a Kernel PCA Model. Meeting of the Association for Computational Linguistics. 88–92.13 indexed citations
18.
Wu, Dekai, Grace Ngai, & Marine Carpuat. (2004). Raising the Bar: Stacked Conservative Error Correction Beyond Boosting.. Language Resources and Evaluation.1 indexed citations
19.
Wicentowski, Richard, et al.. (2004). Joining Forces To Resolve Lexical Ambiguity: East Meets West In Barcelona. Works - Scholarship, Research, & Creative Expression (Swarthmore College). 262–264.1 indexed citations
20.
Carpuat, Marine & Pascale Fung. (2001). CLEF 2001 Bilingual Task: Simple Dictionary-Based Query Translation.. Rare & Special e-Zone (The Hong Kong University of Science and Technology).
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.