Search Results for author: Farhad Akhbardeh

Found 5 papers, 0 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

Transfer Learning Methods for Domain Adaptation in Technical Logbook Datasets

no code implementations LREC 2022 Farhad Akhbardeh, Marcos Zampieri, Cecilia Ovesdotter Alm, Travis Desell

Event identification in technical logbooks poses challenges given the limited logbook data available in specific technical domains, the large set of possible classes, and logbook entries typically being in short form and non-standard technical language.

Domain Adaptation Transfer Learning

Handling Extreme Class Imbalance in Technical Logbook Datasets

no code implementations ACL 2021 Farhad Akhbardeh, Cecilia Ovesdotter Alm, Marcos Zampieri, Travis Desell

In this paper we focus on the problem of technical issue classification by considering logbook datasets from the automotive, aviation, and facilities maintenance domains.

MaintNet: A Collaborative Open-Source Library for Predictive Maintenance Language Resources

no code implementations COLING 2020 Farhad Akhbardeh, Travis Desell, Marcos Zampieri

Furthermore, it provides a way to encourage discussion on and sharing of new datasets and tools for logbook data analysis.


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