A Four-Axis Trustworthiness Benchmark for LLM-as-Judge in Principle-Based Regulation
Principle-based regulation, with evaluative standards such as "fair, clear, and not misleading" or "deliver good outcomes", cannot be reduced to binary predicates, and LLM-as-judge is increasingly used as the substitute. Our position is that any such judge must be evaluated on four axes: accuracy, paraphrase robustness, adversarial robustness, and calibration. We release Principle-Bench, 168 cryptoasset financial-promotion scenarios mapped to two UK FCA principles, with paraphrase, adversarial keyword-stuffing, and boundary perturbations authored under a pre-registered rubric; the first benchm
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- PossiblePossibly related (embedding) · 49%Mastering financial risk and compliance with AI -... - Technology Record →
- PossiblePossibly related (embedding) · 47%FCA’s Mills Review on Artificial Intelligence in retail financial services: More regulatory changes ahead - JD Supra →
- LinkedLinked via arxiv author · 85%Dipankar Sarkar →
“A Four-Axis Trustworthiness Benchmark for LLM-as-Judge in Principle-Based Regulation”
