3 papers
cs.CV2026
NewtPhys: Do Foundation Models Understand Newtonian Physics?
Sebastian Cavada, Soumava Paul, Tuan-Hung Vu +2
Previous work has evaluated physics reasoning in foundation models using synthetic or semi-synthetic scenes and visual question-answering tasks. However, these benchmarks emphasize…
cs.CV2024
CAD-Assistant: Tool-Augmented VLLMs as Generic CAD Task Solvers
Dimitrios Mallis, Ahmet Serdar Karadeniz, Sebastian Cavada +5
We propose CAD-Assistant, a general-purpose CAD agent for AI-assisted design. Our approach is based on a powerful Vision and Large Language Model (VLLM) as a planner and a tool-aug…
cs.CV2024
All Languages Matter: Evaluating LMMs on Culturally Diverse 100 Languages
Ashmal Vayani, Dinura Dissanayake, Hasindri Watawana +66
Existing Large Multimodal Models (LMMs) generally focus on only a few regions and languages. As LMMs continue to improve, it is increasingly important to ensure they understand cul…