HOMADOS at SemEval-2021 Task 6: Multi-Task Learning for Propaganda Detection

Konrad Kaczyński, Piotr Przybyła


Abstract
Among the tasks motivated by the proliferation of misinformation, propaganda detection is particularly challenging due to the deficit of fine-grained manual annotations required to train machine learning models. Here we show how data from other related tasks, including credibility assessment, can be leveraged in multi-task learning (MTL) framework to accelerate the training process. To that end, we design a BERT-based model with multiple output layers, train it in several MTL scenarios and perform evaluation against the SemEval gold standard.
Anthology ID:
2021.semeval-1.141
Volume:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP | SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1027–1031
Language:
URL:
https://aclanthology.org/2021.semeval-1.141
DOI:
10.18653/v1/2021.semeval-1.141
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.141.pdf