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arXiv Computation and Language By Oleksandr Marchenko Breneur, Adelaide Danilov, Aria Nourbakhsh, Salima Lamsiyah

NOTAI.AI: Explainable Detection of Machine-Generated Text via Curvature and Feature Attribution

Read the original on arXiv Computation and Language →

NOTAI.AI is an explainable AI-generated text detection system that goes beyond a simple binary label by showing which signals influenced its prediction. It combines sentence-level conditional probability curvature, a neural detector score, and interpretable stylometric and readability features in an XGBoost meta-classifier, and explains predictions using TreeSHAP feature contributions that can be turned into concise natural-language explanations. Evaluated on a balanced subset of RAID, the full model achieves 0.9685 F1 and receives 94.5–98.6% approval from model judges for the faithfulness of its explanations.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computation and Language.

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