NOTAI.AI: Explainable Detection of Machine-Generated Text via Curvature and Feature Attribution
We present NotAI.AI, an explainable AI-generated text detection system. Instead of returning only a binary label or confidence score, the system shows which signals influenced the prediction and lets users inspect an attribution-based sensitivity estimate obtained by subtracting selected local contributions. NotAI.AI combines sentence-level conditional probability curvature, a neural detector score, and interpretable stylometric and readability features in an XGBoost meta-classifier. It explains predictions with TreeSHAP feature contributions and can turn the resulting evidence into a concise natural-language explanation. We evaluate the system on a category-balanced subset of RAID contai...
| Authors | Oleksandr Marchenko Breneur, Adelaide Danilov, Aria Nourbakhsh et al. |
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| Primary category | cs.CL |
| Published | 5 March 2026 |
| Last updated at source | 3 September 2026 |
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