Xingzhou Pang

Unveiling the Visual Counting Bottleneck in Vision-Language Models

While Large Vision-Language Models (VLMs) excel at interpolation, they suffer catastrophic failures in systematic generalization, most notably in visual counting beyond training distributions. In this work, we investigate this extrapolation bottleneck by deconstructing visual counting into three cog…