D-Score: A Spectral Hidden-State Signal for Hallucination Detection in Large Language Models
Large Language Models can produce fluent text that is false, unsupported by the available evidence, or inconsistent with information that appears to be internally represented by the model. We study hallucination detection from the geometry of hidden activations and introduce the D-Score, a simple spectral statistic computed from a single forward pass. For a fixed model, layer, and tolerance parameter, the D-Score counts how many singular directions of the hidden activation matrix have singular values that remain close to the leading one. We use this quantity as a hallucination score, classifying an input text as hallucinated when its D-Score is larger than a pre-defined quantity. The moti...
| Authors | Bianca Raimondi, Davide Evangelista, Maurizio Gabbrielli et al. |
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| Primary category | cs.CL |
| Published | 27 July 2026 |
| Last updated at source | 27 July 2026 |
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