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Applied to the CM4AI MDA-MB-468 chemical-perturbation atlas comprising 462 antibody labels and SubCell 1536-dimensional embeddings, SVC-Probe demonstrates that 98.6% three-way condition accuracy does not correlate with reliable cross-drug prediction, with cosine similarity diminishing from 0.944 in-domain to 0.30 under leave-o","title":"SVC-Probe: A Framework for Evaluating Perturbation Generalization in Spatial Foundation-Model Embeddings","url":"https://arxiv.org/abs/2606.28465","vendor":"arxiv_cs_ai"},"summary":"arXiv:2606.28465v1 Announce Type: cross \nAbstract: This work examines perturbation generalization in spatial foundation-model embeddings derived from fluorescence microscopy images. Although these models can discriminate drug conditions accurately, it remains unclear whether the learned representations reflect patterns consistent with expected perturbation axes that transfer across drugs. 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