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CAFD: Concept-Aware DNN Fault Detection using VLMs

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arXiv:2605. 24008v1 Announce Type: new Abstract: Fault detection for Deep Neural Networks (DNNs) has received increasing attention in recent years.

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Authors: Amin Abbasishahkoo, Mahboubeh Dadkhah, Lionel Briand
Released: 2026-05-26 (2mo ago)
Topic: Related to current project
Relation to my work: Read next because CAFD: Concept-Aware DNN Fault Detection using VLMs overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: text, eval, source, line, rate, full, trained, language. Source: arxiv cs.LG (Machine Learning).
arXiv: 2605.24008

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