LegalHalluLens introduces a framework to audit AI hallucinations in legal contexts by analyzing typed hallucination profiles across four claim categories. It reveals a 38-40 point gap between obligation/numeric and temporal claims, and shows two systems with identical 52% hallucination rates can have opposite risk directions. The framework uses a Risk Direction Index and calibrated debate pipelines to reduce fabricated detections by 45% and improve accountability in legal AI deployment.
arxiv
arXiv cs.AI
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56d ago
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research
LegalHalluLens: Auditing Hallucinations in Legal AI
from English
Importance 3/3
New feature vs. leaders
New harness with differentiators
arXiv cs.AI
OpenAI
Anthropic
Google DeepMind
AI agents
Reasoning models
Safety & alignment
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