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Enhancing LLM-based Hatred and Toxicity Detection with Meta-Toxic Knowledge Graph
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Meta-Tox is a novel method that first utilizes LLMs to construct a meta-toxic knowledge graph through a three-step pipeline (rationale reasoning, triplet extraction, and entity resolution). Subsequently, it queries this graph via retrieval and ranking to supplement accurate, relevant toxicity knowledge. This knowledge is then used to prompt LLMs, boosting their capability in hatred and toxicity detection during inference, thus demonstrating a unified framework where LLMs act as agents both in building and interacting with the KG for reasoning.
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