Thanks for the precise critique.
You are right: Recall 54% is the "danger zone." In a regulated or production environment, missing half of the structural collapses is functionally equivalent to zero protection. The 88% precision proves the signal exists, but the threshold for "collapse" in latent space is currently too rigid.
The "Geometric approach (SIB) + Rule-based output validation" hybrid you suggested is the most logical path forward.
• Geometric Drift (Layer-Internal): Catches the "process" of losing logical coherence (structural entropy).
• Rule-based (Output-Layer): Catches the "result" of semantic violations (pre-defined constraints).
My next focus is analyzing the "Silent Failures" — the 46% we missed. If the latent space doesn't show geometric collapse but the output is still a hallucination, it suggests the model is confidently drifting into a "parallel" but structurally stable manifold. That's a different failure mode that geometry alone can't catch.
Reproducibility is the only way to move this out of "voodoo AI" territory. Glad the raw_logs.csv helped.
entrustai|23 hours ago
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