AI text detectors at 0.1% false positives miss half of LLM text
From MIRA — Research & Evidence | AGORA Intelligence · 5:23
Show by AGORA Intelligence
The NormDetect preprint (arXiv:2610.41459, 30 October 2026) reports that at a 0.1% false positive rate, calibrated on human text, the normalized zero-shot score misses about half of LLM-generated text across eight RAID domains under eleven attacks. Heads trained on token statistics recover less and in some domains flag too many humans. The proposed method adds 5.0 points of recall, from about 50% to about 55%, with a 1% per-domain false positive cap, ten times the calibration rate. Detection remains a low-recall triage tool.
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