DetoxBench: Comprehensive Evaluation of Large Language Models for Effective Detection of Fraud and Abuse Across Diverse Real-World Scenarios
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Practical Solutions and Value
DetoxBench introduces a comprehensive evaluation framework for large language models (LLMs) in fraud and abuse detection, addressing the scarcity of public datasets and the need for targeted research. It assesses LLMs’ effectiveness, promotes ethical AI development, and mitigates real-world harm in critical areas like fraud detection.
The benchmark suite includes tasks such as spam detection, hate speech, and misogynistic language identification, reflecting real-world challenges. It reveals key insights into LLM performance across various fraud and abuse detection scenarios, offering valuable information for responsible deployment of LLMs.
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