Mitigating Implicit Bias in Chinese Toxic Speech Detection via Unbiased Contrastive Learning

Mitigating human-like biases and social stereotypes in pre-trained language models (PLMs) has become a crucial task in Chinese toxic speech detection. While PLMs have achieved state-of-the-art results in mitigating explicit bias (e.g., bias on sensitive