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Scale-up: An efficient black-box input-level backdoor detection via analyzing scaled prediction consistency,

2 Pith papers cite this work. Polarity classification is still indexing.

2 Pith papers citing it

fields

cs.CR 2

years

2026 2

verdicts

UNVERDICTED 2

representative citing papers

Lightweight and Fast Backdoor Model Detection

cs.CR · 2026-05-17 · unverdicted · novelty 6.0

DFBScanner detects backdoors by combining anomaly indicators from final-layer parameters into a Trojan clue score, reporting 97.17% true-positive rate, 0.95% false-positive rate, and 1 ms average detection time on a benchmark of over 5,000 models.

citing papers explorer

Showing 2 of 2 citing papers.

  • Fast and Lightweight Backdoor Detection via Head Random Probing cs.CR · 2026-05-17 · unverdicted · none · ref 46

    HTell detects backdoors by random probing of the model head, reporting 99.03% true positive rate and 2.11% false positive rate at 12.69 ms per model on a benchmark of over 6700 models.

  • Lightweight and Fast Backdoor Model Detection cs.CR · 2026-05-17 · unverdicted · none · ref 40

    DFBScanner detects backdoors by combining anomaly indicators from final-layer parameters into a Trojan clue score, reporting 97.17% true-positive rate, 0.95% false-positive rate, and 1 ms average detection time on a benchmark of over 5,000 models.