The trained part of JEF, an open System One decision engine: typed questions in, probability distributions with calibrated confidence out, no text generated. This repository is not a standalone model. It holds a bilinear decision head and a fitted calibrator that sit on top of a frozen jhu-clsp/mmBERT-base. That split is why it is ~400KB instead of ~800MB, and why it trains on CPU. Out-of-sample, on a split grouped by evidence rather than by sample — one CVE yields several questions over an identical description, and splitting per sample puts that text on both sides of the line. Test set: 1397 samples. On CTI-Bench VSP, with every training CVE excluded, attack vector reaches 0.840 against a…
Independent publisher
Lee
dennislee928tw
Models in Library1
Datasets in Library0
Models on Hugging Face11
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Published tasks: Text classification.
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