GazeVLM: Active Vision via Internal Attention Control for Multimodal Reasoning
Human visual reasoning is governed by active vision, a process where meta-cognitive control drives top-down goal-directed attention, dynamically routing foveal focus toward task-relevant details while maintaining peripheral awareness of the global scene. In contrast, modern Vision-Language Models (VLMs) process visual information passively, relying on the static accumulation of massive token contexts that dilute the visual evidence as the reasoning chain grows. Here we propose GazeVLM, a VLM that learns to exert this oversight over its attention resources by generating gaze actions in its reasoning chain, in the form of <LOOK> tags specifying the coordinates of the region to inspect. Duri...
| Authors | Brown Ebouky, Gabriele Carrino, Niccolo Avogaro et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 May 2026 |
| Last updated at source | 27 September 2026 |
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