Abstract
We obtain new results using referential translation machines (RTMs) with predictions mixed to obtain a better mixture of experts prediction. Our super learner results improve the results and provide a robust combination model.- Anthology ID:
- 2021.wmt-1.91
- Volume:
- Proceedings of the Sixth Conference on Machine Translation
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Editors:
- Loic Barrault, Ondrej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussa, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Tom Kocmi, Andre Martins, Makoto Morishita, Christof Monz
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 885–889
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.91
- DOI:
- Cite (ACL):
- Ergun Biçici. 2021. RTM Super Learner Results at Quality Estimation Task. In Proceedings of the Sixth Conference on Machine Translation, pages 885–889, Online. Association for Computational Linguistics.
- Cite (Informal):
- RTM Super Learner Results at Quality Estimation Task (Biçici, WMT 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2021.wmt-1.91.pdf