Breaking the Cloak! Unveiling Chinese Cloaked Toxicity with Homophone Graph and Toxic Lexicon

The paper introduces C$^2$TU, a training‑free and prompt‑free method for uncovering Chinese cloaked toxic content. It uses substring matching with a Chinese homophone graph and toxic lexicon to spot candidate toxic words, then filters non‑toxic candidates and corrects cloaks using two variants—one based on BERT and another on LLMs that overcome auto‑regressive limitations. Experiments on two Chinese toxic datasets show C$^2$TU outperforms the best competitor by up to 71% in F1 score and 35% in accuracy.

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• llms
• safety