Do Enterprise Systems Need Learned World Models? The Importance of Context to Infer Dynamics Paper • 2605.12178 • Published 11 days ago • 60
World Action Models: The Next Frontier in Embodied AI Paper • 2605.12090 • Published 11 days ago • 64
When to Trust Imagination: Adaptive Action Execution for World Action Models Paper • 2605.06222 • Published 16 days ago • 42
End-to-End Autoregressive Image Generation with 1D Semantic Tokenizer Paper • 2605.00503 • Published 22 days ago • 11
Image Generators are Generalist Vision Learners Paper • 2604.20329 • Published about 1 month ago • 20
Coevolving Representations in Joint Image-Feature Diffusion Paper • 2604.17492 • Published Apr 19 • 5
Representations Before Pixels: Semantics-Guided Hierarchical Video Prediction Paper • 2604.11707 • Published Apr 13 • 8
Representations Before Pixels: Semantics-Guided Hierarchical Video Prediction Paper • 2604.11707 • Published Apr 13 • 8
Representations Before Pixels: Semantics-Guided Hierarchical Video Prediction Paper • 2604.11707 • Published Apr 13 • 8
ThinkTwice: Jointly Optimizing Large Language Models for Reasoning and Self-Refinement Paper • 2604.01591 • Published Apr 2 • 42
Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models Paper • 2603.25716 • Published Mar 26 • 156
Toward Physically Consistent Driving Video World Models under Challenging Trajectories Paper • 2603.24506 • Published Mar 25 • 6
WildWorld: A Large-Scale Dataset for Dynamic World Modeling with Actions and Explicit State toward Generative ARPG Paper • 2603.23497 • Published Mar 24 • 91
Grounding World Simulation Models in a Real-World Metropolis Paper • 2603.15583 • Published Mar 16 • 154