A systematic review of toxicity in large language models: definitions, datasets, detectors, detoxification methods and challenges

The emergence of the transformer architecture has ushered in a new era of possibilities, showcasing remarkable capabilities in generative tasks exemplified by models like GPT4o, Claude 3, and Llama 3. However, these advancements come with a caveat: predominantly trained on data gleaned from social media platforms, these systems inadvertently perpetuate societal biases and toxicity. Recognizing the paramount importance of AI Safety and Alignment, our study embarks on a thorough exploration throug

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ethics.ai (2 July 2026), “A systematic review of toxicity in large language models: definitions, datasets, detectors, detoxification methods and challenges,” evidence record 1990, https://ethics.ai/record/1990 (originally published by Artificial Intelligence Review).

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