AURORA detects hallucinations via skewness of cosine similarities between weights and gradients plus a rotation ratio from SVD on update-induced changes to singular vectors.
Proceedings of the AAAI Conference on Artificial Intelligence , author=
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AURORA: Asymmetry and Update-Induced Rotation for Robust Hallucination Detection in Large Language Models
AURORA detects hallucinations via skewness of cosine similarities between weights and gradients plus a rotation ratio from SVD on update-induced changes to singular vectors.