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Patching the Blind Spots: Reversible LLM Rule Overlay for Frozen Fraud Detectors
arXiv cs.CL — Computation and Language
Factual evidence
What the source reports
Researchers introduced a framework using LLMs to generate reversible rule overlays for frozen tabular fraud detection models.
Inspect the evidence
- Inclusion basis
- Enterprise AI
- Publisher and source type
- arXiv cs.CL — Computation and Language · RESEARCH
- Published by source
- 9 November 2026
- Collected by OneBench
- 10 Nov 2026, 02:01 UK
Stored source excerpt
arXiv:2611.08714v1 Announce Type: cross Abstract: In industrial tabular fraud classification, gradient-boosted trees remain state-of-the-art, but even a well-trained model has blind spots, and retraining the…
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