New AI Detection Framework REVEAL Uses Reasoning Chains and Reinforcement Learning

A new detection framework called REVEAL has been developed to identify AI-generated content with improved accuracy and transparency. The system employs a two-stage training approach that begins with supervised fine-tuning to build reasoning capabilities, then uses reinforcement learning to enhance performance. This method specifically aims to reduce hallucinations and improve logical consistency in detection outputs. REVEAL generates interpretable reasoning chains before making classification decisions, providing more transparent detection processes. The framework was tested using the AIGC-text-bank dataset, which contains diverse LLM sources and authorship scenarios across multiple domains. Extensive experiments demonstrate that REVEAL achieves state-of-the-art performance across various benchmarks. The project has been made open-source and is available through a provided URL. This development addresses the growing challenge of reliable AI-generated content detection as large language models continue to evolve and become more widely adopted.