Among all MLLMs, proprietary models consistently perform well.

To perform systematic evaluations, we set up 32 various tasks, including improvements to existing multimodal tasks, extension of text-only tasks to multimodal scenarios, and novel methods for risk assessment, which focus on models' basic performance with practical significance.

To evaluate MLLMs' A VR abilities systematically, we introduce

In this work, we introduce Scribbles for All, a label and training data generation algorithm for semantic segmentation trained on scribble labels.