متابعة
Chris Callison-Burch
Chris Callison-Burch
Professor, University of Pennsylvania
بريد إلكتروني تم التحقق منه على upenn.edu - الصفحة الرئيسية
عنوان
عدد مرات الاقتباسات
عدد مرات الاقتباسات
السنة
Moses: Open source toolkit for statistical machine translation‏
P Koehn, H Hoang, A Birch, C Callison-Burch, M Federico, N Bertoldi, ...‏
Proceedings of the 45th annual meeting of the association for computational …, 2007‏
73592007
Beyond the imitation game: Quantifying and extrapolating the capabilities of language models‏
A Srivastava, A Rastogi, A Rao, AAM Shoeb, A Abid, A Fisch, AR Brown, ...‏
arXiv preprint arXiv:2206.04615, 2022‏
12932022
Re-evaluating the role of BLEU in machine translation research‏
C Callison-Burch, M Osborne, P Koehn‏
Proceedings of EACL 2006, 249-256, 2006‏
11162006
PPDB: The paraphrase database‏
J Ganitkevitch, B Van Durme, C Callison-Burch‏
Proceedings of NAACL-HLT, 758-764, 2013‏
9762013
Findings of the 2009 workshop on statistical machine translation‏
C Callison-Burch, P Koehn, C Monz, J Schroeder‏
8602009
Paraphrasing with bilingual parallel corpora‏
C Bannard, C Callison-Burch‏
Proceedings of the 43rd Annual Meeting on Association for Computational …, 2005‏
8012005
A data-driven analysis of workers' earnings on Amazon Mechanical Turk‏
K Hara, A Adams, K Milland, S Savage, C Callison-Burch, JP Bigham‏
Proceedings of the 2018 CHI conference on human factors in computing systems …, 2018‏
7402018
Optimizing statistical machine translation for text simplification‏
W Xu, C Napoles, E Pavlick, Q Chen, C Callison-Burch‏
Transactions of the Association for Computational Linguistics 4, 401-415, 2016‏
7052016
Method and apparatus for providing multilingual translation over a network‏
J Chin, C Callison-Burch, R Flournoy, P Hidisyan, R Horiuchi, Y Kassum, ...‏
US Patent App. 09/825,437, 2001‏
6722001
Fast, cheap, and creative: Evaluating translation quality using Amazon’s Mechanical Turk‏
C Callison-Burch‏
Proceedings of the 2009 conference on empirical methods in natural language …, 2009‏
6642009
Deduplicating training data makes language models better‏
K Lee, D Ippolito, A Nystrom, C Zhang, D Eck, C Callison-Burch, N Carlini‏
arXiv preprint arXiv:2107.06499, 2021‏
5882021
Problems in current text simplification research: New data can help‏
W Xu, C Callison-Burch, C Napoles‏
Transactions of the Association for Computational Linguistics 3, 283-297, 2015‏
5372015
Crowdsourcing translation: professional quality from non-professionals‏
OF Zaidan, C Callison-Burch‏
Proceedings of ACL (this volume), 2011‏
5302011
Edinburgh system description for the 2005 IWSLT speech translation evaluation‏
P Koehn, A Axelrod, AB Mayne, C Callison-Burch, M Osborne, D Talbot‏
International Workshop on Spoken Language Translation, 2005‏
4602005
Creating speech and language data with amazon’s mechanical turk‏
C Callison-Burch, M Dredze‏
Proceedings of the NAACL HLT 2010 workshop on creating speech and language …, 2010‏
4472010
Arabic dialect identification‏
OF Zaidan, C Callison-Burch‏
Computational Linguistics 40 (1), 171-202, 2014‏
4322014
Improved statistical machine translation using paraphrases‏
C Callison-Burch, P Koehn, M Osborne‏
Proceedings of the Human Language Technology Conference of the NAACL, Main …, 2006‏
4032006
PPDB 2.0: Better paraphrase ranking, fine-grained entailment relations, word embeddings, and style classification‏
E Pavlick, P Rastogi, J Ganitkevitch, B Van Durme, C Callison-Burch‏
Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015‏
3952015
Automatic detection of generated text is easiest when humans are fooled‏
D Ippolito, D Duckworth, C Callison-Burch, D Eck‏
arXiv preprint arXiv:1911.00650, 2019‏
3662019
Further meta-evaluation of machine translation‏
C Callison-Burch, C Fordyce, P Koehn, C Monz, J Schroeder‏
Proceedings of the Third Workshop on Statistical Machine Translation, 70-106, 2008‏
3162008
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مقالات 1–20