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arxiv logo>cs> arXiv:2412.11691
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Computer Science > Computation and Language

arXiv:2412.11691 (cs)
[Submitted on 16 Dec 2024]

Title:Multilingual and Explainable Text Detoxification with Parallel Corpora

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Abstract:Even with various regulations in place across countries and social media platforms (Government of India, 2021; European Parliament and Council of the European Union, 2022, digital abusive speech remains a significant issue. One potential approach to address this challenge is automatic text detoxification, a text style transfer (TST) approach that transforms toxic language into a more neutral or non-toxic form. To date, the availability of parallel corpora for the text detoxification task (Logachevavet al., 2022; Atwell et al., 2022; Dementievavet al., 2024a) has proven to be crucial for state-of-the-art approaches. With this work, we extend parallel text detoxification corpus to new languages -- German, Chinese, Arabic, Hindi, and Amharic -- testing in the extensive multilingual setup TST baselines. Next, we conduct the first of its kind an automated, explainable analysis of the descriptive features of both toxic and non-toxic sentences, diving deeply into the nuances, similarities, and differences of toxicity and detoxification across 9 languages. Finally, based on the obtained insights, we experiment with a novel text detoxification method inspired by the Chain-of-Thoughts reasoning approach, enhancing the prompting process through clustering on relevant descriptive attributes.
Comments:COLING 2025, main conference, long
Subjects:Computation and Language (cs.CL); Artificial Intelligence (cs.AI)
Cite as:arXiv:2412.11691 [cs.CL]
 (orarXiv:2412.11691v1 [cs.CL] for this version)
 https://doi.org/10.48550/arXiv.2412.11691
arXiv-issued DOI via DataCite

Submission history

From: Daryna Dementieva [view email]
[v1] Mon, 16 Dec 2024 12:08:59 UTC (10,316 KB)
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