Josif Grabocka

Pretrained tabular foundation models, when adapted with a simple readout and contrastive learning, unlock state-of-the-art dataset representations for retrieval and shift detection.

MLLMs struggle to ground cultural values in visual scenes, losing ~7% accuracy compared to text-only inputs, even when they understand the visual content.