PAN: A World Model for General, Actionable, and Long-Horizon World Simulation
Read the original on arXiv AI →The Flow has not summarised this story yet — read it at arXiv AI.
The Flow has not summarised this story yet — read it at arXiv AI.
WorldCast is a benchmark that tests multimodal generative models on multi-step world state prediction, requiring them to forecast successive future states from multimodal observations and diverse references. The study evaluates 12 models across 320 manually designed cases in eight categories, revealing that advanced models like GPT-Image-2.5 achieve high scores while open-source models lag behind, especially on complex context and reasoning tasks. The results underscore the importance of integrating dynamic planning, reasoning, and unified multimodal capabilities for realistic world simulation.
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