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News/LLM-FACETS: A Privacy-Preserving Framework for Evaluating LLM Transparency and Accountability
arxiv
PublishedJune 1, 2026 at 4:00 AM

LLM-FACETS: A Privacy-Preserving Framework for Evaluating LLM Transparency and Accountability

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arXiv:2605.31167v1 Announce Type: new Abstract: Assessing whether Large Language Models outputs are factually grounded, epistemically calibrated, and methodologically reproducible is a prerequisite for responsible AI deployment. Yet auditing LLMs remains inaccessible to non-technical practitioners:

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