Mitigating Bias in Conversations: A Hate Speech Classifier and Debiaser with Prompts
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Abstract (arXiv)
Discriminatory language and biases are often present in hate speech during conversations, which usually lead to negative impacts on targeted groups such as those based on race, gender, and religion. To tackle this issue, we propose an approach that involves a two-step process: first, detecting hate speech using a classifier, and then utilizing a debiasing component that generates less biased or unbiased alternatives through prompts. We evaluated our approach on a benchmark dataset and observed reduction in negativity due to hate speech comments. The proposed method contributes to the ongoing efforts to reduce biases in online discourse and promote a more inclusive and fair environment for communication.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 17 of its 22 references that are in the map. First posted on arXiv 14 Jul 2023.
Builds on
17 of 22 references.
References · 17
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- 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,222
- 2016Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddingscited by 1,304
- 2020StereoSet: Measuring stereotypical bias in pretrained language modelscited by 911
- 2016Semantics derived automatically from language corpora contain human-like biasescited by 894
- 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 724
- 2023Instruction Tuning with GPT-4cited by 676
- 2021Persistent Anti-Muslim Bias in Large Language Modelscited by 376
- 2022"I'm sorry to hear that": Finding New Biases in Language Models with a Holistic Descriptor Datasetcited by 160
- 2021RedditBias: A Real-World Resource for Bias Evaluation and Debiasing of Conversational Language Modelscited by 149
- 2019Reducing Sentiment Bias in Language Models via Counterfactual Evaluationcited by 148
- 2020Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Biascited by 82
5 more
- 2021Mitigating Political Bias in Language Models Through Reinforced Calibrationcited by 73
- 2022Handling Bias in Toxic Speech Detection: A Surveycited by 60
- 2021Hate Towards the Political Opponent: A Twitter Corpus Study of the 2020 US Elections on the Basis of Offensive Speech and Stance Detectioncited by 45
- 2022Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversalcited by 40
- 2022Dbias: Detecting biases and ensuring Fairness in news articlescited by 28
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