DE eng

Search in the Catalogues and Directories

Hits 1 – 2 of 2

1
deepQuest-py: large and distilled models for quality estimation
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations ; 382 ; 389 (2021)
Abstract: © (2021) The Authors. Published by Association for Computational Linguistics. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://aclanthology.org/2021.emnlp-demo.42/ ; We introduce deepQuest-py, a framework for training and evaluation of large and lightweight models for Quality Estimation (QE). deepQuest-py provides access to (1) state-ofthe-art models based on pre-trained Transformers for sentence-level and word-level QE; (2) light-weight and efficient sentence-level models implemented via knowledge distillation; and (3) a web interface for testing models and visualising their predictions. deepQuestpy is available at https://github.com/ sheffieldnlp/deepQuest-py under a CC BY-NC-SA licence.
Keyword: machine translation; quality estimation
URL: http://hdl.handle.net/2436/624377
https://doi.org/10.18653/v1/2021.emnlp-demo.42
BASE
Hide details
2
Knowledge distillation for quality estimation
In: 5091 ; 5099 (2021)
BASE
Show details

Catalogues
0
0
0
0
0
0
0
Bibliographies
0
0
0
0
0
0
0
0
0
Linked Open Data catalogues
0
Online resources
0
0
0
0
Open access documents
2
0
0
0
0
© 2013 - 2024 Lin|gu|is|tik | Imprint | Privacy Policy | Datenschutzeinstellungen ändern