CounterGeDi: A controllable approach to generate polite, detoxified and emotional counterspeech

Understand

Recently, many studies have tried to create generation models to assist counter speakers by providing counterspeech suggestions for combating the explosive proliferation of online hate.

• However, since these suggestions are from a vanilla generation model, they might not include the appropriate properties required to counter a particular hate speech instance.
• In this paper, we propose CounterGeDi - an ensemble of generative discriminators (GeDi) to guide the generation of a DialoGPT model toward more polite, detoxified, and emotionally laden counterspeech.
• We generate counterspeech using three datasets and observe significant improvement across different attribute scores.