DeepSPIN: Deep Structured Prediction for Natural Language Processing
André F. T. Martins, Ben Peters, Chrysoula Zerva, Chunchuan Lyu, Gonçalo Correia, Marcos Treviso, Pedro Martins, Tsvetomila Mihaylova
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. We describe in this paper the latest findings from this project.- Anthology ID:
- 2022.eamt-1.53
- Volume:
- Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
- Month:
- June
- Year:
- 2022
- Address:
- Ghent, Belgium
- Editors:
- Helena Moniz, Lieve Macken, Andrew Rufener, Loïc Barrault, Marta R. Costa-jussà, Christophe Declercq, Maarit Koponen, Ellie Kemp, Spyridon Pilos, Mikel L. Forcada, Carolina Scarton, Joachim Van den Bogaert, Joke Daems, Arda Tezcan, Bram Vanroy, Margot Fonteyne
- Venue:
- EAMT
- SIG:
- Publisher:
- European Association for Machine Translation
- Note:
- Pages:
- 327–328
- Language:
- URL:
- https://aclanthology.org/2022.eamt-1.53
- DOI:
- Cite (ACL):
- André F. T. Martins, Ben Peters, Chrysoula Zerva, Chunchuan Lyu, Gonçalo Correia, Marcos Treviso, Pedro Martins, and Tsvetomila Mihaylova. 2022. DeepSPIN: Deep Structured Prediction for Natural Language Processing. In Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, pages 327–328, Ghent, Belgium. European Association for Machine Translation.
- Cite (Informal):
- DeepSPIN: Deep Structured Prediction for Natural Language Processing (Martins et al., EAMT 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.eamt-1.53.pdf