DeepSPIN: Deep Structured Prediction for Natural Language Processing

André F. T. Martins


Abstract
DeepSPIN is a research project funded by the European Research Council (ERC) whose goal is to develop new neural structured prediction methods, models, and algorithms for improving the quality, interpretability, and data-efficiency of natural language processing (NLP) systems, with special emphasis on machine translation and quality estimation applications.
Anthology ID:
2020.eamt-1.67
Volume:
Proceedings of the 22nd Annual Conference of the European Association for Machine Translation
Month:
November
Year:
2020
Address:
Lisboa, Portugal
Editors:
André Martins, Helena Moniz, Sara Fumega, Bruno Martins, Fernando Batista, Luisa Coheur, Carla Parra, Isabel Trancoso, Marco Turchi, Arianna Bisazza, Joss Moorkens, Ana Guerberof, Mary Nurminen, Lena Marg, Mikel L. Forcada
Venue:
EAMT
SIG:
Publisher:
European Association for Machine Translation
Note:
Pages:
493–494
Language:
URL:
https://aclanthology.org/2020.eamt-1.67
DOI:
Bibkey:
Cite (ACL):
André F. T. Martins. 2020. DeepSPIN: Deep Structured Prediction for Natural Language Processing. In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, pages 493–494, Lisboa, Portugal. European Association for Machine Translation.
Cite (Informal):
DeepSPIN: Deep Structured Prediction for Natural Language Processing (Martins, EAMT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.eamt-1.67.pdf