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:
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.eamt-1.67.pdf