Search Results for author: Christopher Homan

Found 13 papers, 1 papers with code

Findings of the 2021 Conference on Machine Translation (WMT21)

no code implementations WMT (EMNLP) 2021 Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, Ondřej Bojar, Rajen Chatterjee, Vishrav Chaudhary, Marta R. Costa-Jussa, Cristina España-Bonet, Angela Fan, Christian Federmann, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Leonie Harter, Kenneth Heafield, Christopher Homan, Matthias Huck, Kwabena Amponsah-Kaakyire, Jungo Kasai, Daniel Khashabi, Kevin Knight, Tom Kocmi, Philipp Koehn, Nicholas Lourie, Christof Monz, Makoto Morishita, Masaaki Nagata, Ajay Nagesh, Toshiaki Nakazawa, Matteo Negri, Santanu Pal, Allahsera Auguste Tapo, Marco Turchi, Valentin Vydrin, Marcos Zampieri

This paper presents the results of the newstranslation task, the multilingual low-resourcetranslation for Indo-European languages, thetriangular translation task, and the automaticpost-editing task organised as part of the Con-ference on Machine Translation (WMT) 2021. In the news task, participants were asked tobuild machine translation systems for any of10 language pairs, to be evaluated on test setsconsisting mainly of news stories.

Machine Translation Test +1

A Framework to Assess (Dis)agreement Among Diverse Rater Groups

no code implementations9 Nov 2023 Vinodkumar Prabhakaran, Christopher Homan, Lora Aroyo, Alicia Parrish, Alex Taylor, Mark Díaz, Ding Wang

Recent advancements in conversational AI have created an urgent need for safety guardrails that prevent users from being exposed to offensive and dangerous content.


Sensing and Learning Human Annotators Engaged in Narrative Sensemaking

no code implementations NAACL 2018 McKenna Tornblad, Luke Lapresi, Christopher Homan, Raymond Ptucha, Cecilia Ovesdotter Alm

While labor issues and quality assurance in crowdwork are increasingly studied, how annotators make sense of texts and how they are personally impacted by doing so are not.

Analyzing Gender Bias in Student Evaluations

no code implementations COLING 2016 Andamlak Terkik, Emily Prud{'}hommeaux, Cecilia Ovesdotter Alm, Christopher Homan, Scott Franklin

University students in the United States are routinely asked to provide feedback on the quality of the instruction they have received.

Sentiment Analysis

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