Grid2Matrix: Revealing Digital Agnosia in Vision-Language Models

arXiv:2604.09687v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) excel on many multimodal reasoning benchmarks, but these evaluations often do not require an exhaustive readout of the image and can therefore obscure failures in faithfully capturing all visual details. We...