MultiWorld is a scalable framework for multi-agent multi-view video world models that improves controllability and consistency over single-agent baselines in game and robot tasks.
arXiv preprint arXiv: 2512.12751 (2025) 4
3 Pith papers cite this work. Polarity classification is still indexing.
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EO-WM is a diffusion transformer that adds physically separated baseline-anomaly and cumulative-stress conditioning to probabilistic EO forecasting and validates it on two new weather-response benchmarks, reporting 5.63% and 7.80% relative gains on NDVI decline metrics.
AnyScene is an occupancy-centric framework using a Spatial-Temporal Occupancy Diffusion Transformer and Geometry-Grounded View Expansion to generate controllable driving scenes and videos from BEV layouts.
citing papers explorer
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MultiWorld: Scalable Multi-Agent Multi-View Video World Models
MultiWorld is a scalable framework for multi-agent multi-view video world models that improves controllability and consistency over single-agent baselines in game and robot tasks.
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EO-WM: A Physically Informed World Model for Probabilistic Earth Observation Forecasting
EO-WM is a diffusion transformer that adds physically separated baseline-anomaly and cumulative-stress conditioning to probabilistic EO forecasting and validates it on two new weather-response benchmarks, reporting 5.63% and 7.80% relative gains on NDVI decline metrics.
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AnyScene: Towards Highly Controllable Driving Scene Generation at Anywhere and Beyond
AnyScene is an occupancy-centric framework using a Spatial-Temporal Occupancy Diffusion Transformer and Geometry-Grounded View Expansion to generate controllable driving scenes and videos from BEV layouts.