Impact of COVID-19 in Natural Language Processing Publications: a Disaggregated Study in Gender, Contribution and Experience

no code implementations • EACL (LTEDI) 2021 • Christine Basta, Marta R. Costa-Jussa

This study sheds light on the effects of COVID-19 in the particular field of Computational Linguistics and Natural Language Processing within Artificial Intelligence.

Multi-Task Learning for Improving Gender Accuracy in Neural Machine Translation

no code implementations • ICON 2021 • Carlos Escolano, Graciela Ojeda, Christine Basta, Marta R. Costa-Jussa

Machine Translation is highly impacted by social biases present in data sets, indicating that it reflects and amplifies stereotypes.

Machine Translation Multi-Task Learning +1

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 Translation

The TALP-UPC Participation in WMT21 News Translation Task: an mBART-based NMT Approach

no code implementations • WMT (EMNLP) 2021 • Carlos Escolano, Ioannis Tsiamas, Christine Basta, Javier Ferrando, Marta R. Costa-Jussa, José A. R. Fonollosa

We fine-tune mBART50 using the filtered data, and additionally, we train a Transformer model on the same data from scratch.

Machine Translation NMT +1

Results from the ML4HMT-12 Shared Task on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid Machine Translation

no code implementations • WS 2012 • Christian Federmann, Tsuyoshi Okita, Maite Melero, Marta R. Costa-Jussa, Toni Badia, Josef van Genabith

Machine Translation