mlsanityData to 7 Oct 2026

Hallucination Detection in Virtually-Stained Histology: A Latent Space Baseline

arXiv 2411.15060 ↗First posted 22 Nov 2024eess.IV cs.CV cs.LGcited by 0

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Abstract (arXiv)

Histopathologic analysis of stained tissue remains central to biomedical research and clinical care. Virtual staining (VS) offers a promising alternative, with potential to reduce costs and streamline workflows, yet hallucinations pose serious risks to clinical reliability. Here, we formalize the problem of hallucination detection in VS and propose a scalable post-hoc method: Neural Hallucination Precursor (NHP), which leverages the generator's latent space to preemptively flag hallucinations. Extensive experiments across diverse VS tasks show NHP is both effective and robust. Critically, we also find that models with fewer hallucinations do not necessarily offer better detectability, exposing a gap in current VS evaluation and underscoring the need for hallucination detection benchmarks.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 63 of its 91 references that are in the map. First posted on arXiv 22 Nov 2024.

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63 of 91 references.

References · 63

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