Generalization of CVSearch Across Visual Experts

Determine the generalization capability of the CVSearch framework when the visual expert module is replaced with or combined with visual foundation models other than SAM 3, by integrating alternative visual experts into CVSearch’s Visual Expert Assisted Search and evaluating whether the overall system maintains performance and robustness across these different expert integrations.

Background

CVSearch introduces a training-free cognitive visual search framework that alternates between a visual expert–assisted mode and a scene-aware scanning mode to handle high-resolution image perception. In all reported experiments, the external visual expert responsible for region proposals is SAM 3.

Because the method relies on the expert both for fast localization and for semantic features that guide adaptive patching, substituting different visual expert backbones could affect both proposal quality and the downstream scanning process. The paper notes that this aspect has not yet been studied, leaving open whether CVSearch’s accuracy and efficiency gains persist when using other visual foundation models.

References

Consequently, the generalization capability of the framework when integrated with different types of visual experts remains unexplored.

— CVSearch: Empowering Multimodal LLMs with Cognitive Visual Search for High-Resolution Image Perception  (2605.23655 - Li et al., 22 May 2026) in Limitations