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arXiv Computer Vision By Xinge Peng, Yiting Lu, Tianwu Zhi, Wen Wen, Jianzhao Liu, Xin Li, Zhibo Chen

PhysVista: Benchmarking Physical Intelligence in VLMs via a Perception-Reasoning-Assessment Loop

Read the original on arXiv Computer Vision →

PhysVista is a new benchmark that evaluates physical intelligence in Vision‑Language Models (VLMs) by integrating perception, reasoning, and plausibility assessment into a closed cognitive loop. It distinguishes between event‑level and scale‑level reasoning and tests models on both real‑world and AI‑generated videos to provide a holistic, fine‑grained analysis of physical understanding. Experiments show significant gaps in VLMs’ physical reasoning and plausibility assessment, underscoring the need for more principled, physically grounded multimodal designs.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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