UmBERTo-MTSA @ AcCompl-It: Improving Complexity and Acceptability Prediction with Multi-task Learning on Self-Supervised Annotations (short paper)

Gabriele Sarti


Anthology ID:
2020.evalita-1.70
Volume:
Proceedings of the Seventh Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2020)
Month:
December
Year:
2020
Address:
Online
Editors:
Valerio Basile, Danilo Croce, Maria Di Maro, Lucia C. Passaro
Venues:
EVALITA | WS
SIG:
Publisher:
CEUR Workshop Proceedings
Note:
Pages:
424–429
Language:
URL:
https://aclanthology.org/2020.evalita-1.70/
DOI:
Bibkey:
Cite (ACL):
Gabriele Sarti. 2020. UmBERTo-MTSA @ AcCompl-It: Improving Complexity and Acceptability Prediction with Multi-task Learning on Self-Supervised Annotations (short paper). In Proceedings of the Seventh Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop (EVALITA 2020), pages 424–429, Online. CEUR Workshop Proceedings.
Cite (Informal):
UmBERTo-MTSA @ AcCompl-It: Improving Complexity and Acceptability Prediction with Multi-task Learning on Self-Supervised Annotations (short paper) (Sarti, EVALITA 2020)
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PDF:
https://aclanthology.org/2020.evalita-1.70.pdf