Reasoning-Aware AIGC Detection via Alignment and Reinforcement

• URL: http://arxiv.org/abs/2604.19172v1
• Date: Tue, 21 Apr 2026 07:29:55 GMT
• Title: Reasoning-Aware AIGC Detection via Alignment and Reinforcement
• Abstract summary: REVEAL is a framework that generates interpretable reasoning chains before classification.<n>It achieves state-of-the-art performance across multiple benchmarks.
• Score: 55.09684020007737
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The rapid advancement and widespread adoption of Large Language Models (LLMs) have elevated the need for reliable AI-generated content (AIGC) detection, which remains challenging as models evolve. We introduce AIGC-text-bank, a comprehensive multi-domain dataset with diverse LLM sources and authorship scenarios, and propose REVEAL, a detection framework that generates interpretable reasoning chains before classification. Our approach uses a two-stage training strategy: supervised fine-tuning to establish reasoning capabilities, followed by reinforcement learning to improve accuracy, improve logical consistency, and reduce hallucinations. Extensive experiments show that REVEAL achieves state-of-the-art performance across multiple benchmarks, offering a robust and transparent solution for AIGC detection. The project is open-source at https://aka.ms/reveal

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