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cs.CV2026
Video2World: Benchmarking Coding Agents for Interactive World Modeling from Embodied Videos
Jinzhou Tang, Zijun Zhang, Jing Yang +10
Building interactive simulators from real-world observations is a promising way to scale embodied data, but current pipelines still rely heavily on manual environment construction…
cs.CV2026
Causally Debiased Latent Action Model for Embodied Action-Conditioned World Models
Yufan Wei, Kun Zhou, Lingjun Mao +9
Action-conditioned world models (ACWMs) aim to simulate future observations conditioned on embodied actions. However, learning controllable ACWMs requires large-scale action-labele…
cs.CV2026
DreamSAC: Learning Hamiltonian World Models via Symmetry Exploration
Jinzhou Tang, Fan Feng, Minghao Fu +3
Learned world models excel at interpolative generalization but fail at extrapolative generalization to novel physical properties. This limitation arises because they learn statisti…