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Relational Over-Regularization: Graph-Based AI-Generated Text Detection via Sentence Transition Deviation

arXiv · AI, language, vision and robotics · article · Aug 27, 2026 · UTC

Detecting AI-generated text (AIGT) remains challenging because existing approaches rely on token-level statistical signals or independent stylometric features, causing them to overfit to specific generators and fail under distribution shift. We identify a structural signal at the sentence-pair level: LLMs produce inter-sentence transition variance that deviates from human writing through inflated variance driven by recurring similarity bursts at paragraph boundaries and templated transitions. We formalize this as Relational Over-Regularization (ROR) and validate it across four benchmarks (p <

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