Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study

Serra Sinem Tekiroğlu, Helena Bonaldi, Margherita Fanton, Marco Guerini

Abstract
In this work, we present an extensive study on the use of pre-trained language models for the task of automatic Counter Narrative (CN) generation to fight online hate speech in English. We first present a comparative study to determine whether there is a particular Language Model (or class of LMs) and a particular decoding mechanism that are the most appropriate to generate CNs. Findings show that autoregressive models combined with stochastic decodings are the most promising. We then investigate how an LM performs in generating a CN with regard to an unseen target of hate. We find out that a key element for successful ‘out of target’ experiments is not an overall similarity with the training data but the presence of a specific subset of training data, i. e. a target that shares some commonalities with the test target that can be defined a-priori. We finally introduce the idea of a pipeline based on the addition of an automatic post-editing step to refine generated CNs.
Anthology ID:
2022.findings-acl.245
Volume:
Findings of the Association for Computational Linguistics: ACL 2022
Month:
May
Year:
2022
Address:
Dublin, Ireland
Editors:
Smaranda Muresan, Preslav Nakov, Aline Villavicencio
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
3099–3114
Language:
URL:
https://aclanthology.org/2022.findings-acl.245
DOI:
10.18653/v1/2022.findings-acl.245
Bibkey:
Cite (ACL):
Serra Sinem Tekiroğlu, Helena Bonaldi, Margherita Fanton, and Marco Guerini. 2022. Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study. In Findings of the Association for Computational Linguistics: ACL 2022, pages 3099–3114, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Study (Tekiroğlu et al., Findings 2022)
Copy Citation:
PDF:
https://preview.aclanthology.org/naacl24-info/2022.findings-acl.245.pdf
PDF Search