@inproceedings{gertner-etal-2019-mitre,
title = "{MITRE} at {S}em{E}val-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection",
author = "Gertner, Abigail and
Henderson, John and
Merkhofer, Elizabeth and
Marsh, Amy and
Wellner, Ben and
Zarrella, Guido",
editor = "May, Jonathan and
Shutova, Ekaterina and
Herbelot, Aurelie and
Zhu, Xiaodan and
Apidianaki, Marianna and
Mohammad, Saif M.",
booktitle = "Proceedings of the 13th International Workshop on Semantic Evaluation",
month = jun,
year = "2019",
address = "Minneapolis, Minnesota, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/S19-2080",
doi = "10.18653/v1/S19-2080",
pages = "453--459",
abstract = "This paper describes MITRE{'}s participation in SemEval-2019 Task 5, HatEval: Multilingual detection of hate speech against immigrants and women in Twitter. The techniques explored range from simple bag-of-ngrams classifiers to neural architectures with varied attention mechanisms. We describe several styles of transfer learning from auxiliary tasks, including a novel method for adapting pre-trained BERT models to Twitter data. Logistic regression ties the systems together into an ensemble submitted for evaluation. The resulting system was used to produce predictions for all four HatEval subtasks, achieving the best mean rank of all teams that participated in all four conditions.",
}
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%0 Conference Proceedings
%T MITRE at SemEval-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection
%A Gertner, Abigail
%A Henderson, John
%A Merkhofer, Elizabeth
%A Marsh, Amy
%A Wellner, Ben
%A Zarrella, Guido
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F gertner-etal-2019-mitre
%X This paper describes MITRE’s participation in SemEval-2019 Task 5, HatEval: Multilingual detection of hate speech against immigrants and women in Twitter. The techniques explored range from simple bag-of-ngrams classifiers to neural architectures with varied attention mechanisms. We describe several styles of transfer learning from auxiliary tasks, including a novel method for adapting pre-trained BERT models to Twitter data. Logistic regression ties the systems together into an ensemble submitted for evaluation. The resulting system was used to produce predictions for all four HatEval subtasks, achieving the best mean rank of all teams that participated in all four conditions.
%R 10.18653/v1/S19-2080
%U https://aclanthology.org/S19-2080
%U https://doi.org/10.18653/v1/S19-2080
%P 453-459
Markdown (Informal)
[MITRE at SemEval-2019 Task 5: Transfer Learning for Multilingual Hate Speech Detection](https://aclanthology.org/S19-2080) (Gertner et al., SemEval 2019)
ACL