GPT-DETOX: An In-Context Learning-Based Paraphraser for Text Detoxification

arXiv:2404.03052v1 Announce Type: new
Abstract: Harmful and offensive communication or content is detrimental to social bonding and the mental state of users on social media platforms. Text detoxification is a crucial task in natural language processing (NLP), where the goal is removing profanity and toxicity from text while preserving its content. Supervised and unsupervised learning are common approaches for designing text detoxification solutions. However, these methods necessitate fine-tuning, leading to computational overhead. In this paper, we propose GPT-DETOX as a …

abstract arxiv communication context cs.cl gpt in-context learning language language processing media natural natural language natural language processing nlp platforms processing social social media social media platforms state text toxicity type