arXiv: cs.AI preprintsInternational6 November 2026
InnerLogic-Surg: An Open Surgical Foundation Model via Continual Pretraining
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arXiv:2611.07883v1 Announce Type: cross Abstract: Vision foundation models are the backbone of modern surgical image analysis, yet most surgical systems still rely on encoders pretrained on natural images or on specialist models trained from scratch on comparatively small datasets. Pretraining encoders on large amounts of surgery-specific data has the potential to generally enhance the performance of surgical image analysis methods simply by providing stronger backbones. Here we present InnerLogic-Surg, an open family of surgical vision encoders (21M--300M parameters) obtained by continually p
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