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Detecting Harmful Content at Scale // Matar Haller // #246

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Challenges in Using Transformer Models for Detecting Harmful Content

The chapter explores the difficulties in utilizing transformer models and LLMs for detecting hate speech, emphasizing the necessity of accuracy and monitoring for model drift. It covers auditing processes, testing methodologies, and continuous monitoring post-production to maintain high performance levels in detecting harmful content at scale.

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