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cs.RO2026
VIDEAS: Distilling Explicit Action Semantics from Demonstration Videos for World Models via Prior-Guided Simulation
Jianan Wang, Haoquan Zhai, Siyang Zhang +7
World models learn internal representations of environment dynamics to predict future states, enabling agents to optimize action plans without physical interactions. However, devel…
cs.RO2026
LogicEnvGen: Task-Logic Driven Generation of Diverse Simulated Environments for Embodied AI
Jianan Wang, Siyang Zhang, Bin Li +4
Simulated environments play an essential role in embodied AI, functionally analogous to test cases in software engineering. However, existing environment generation methods often e…
cs.RO2025
VITA-E: Natural Embodied Interaction with Concurrent Seeing, Hearing, Speaking, and Acting
Xiaoyu Liu, Chaoyou Fu, Chi Yan +15
Current Vision-Language-Action (VLA) models are often constrained by a rigid, static interaction paradigm, which lacks the ability to see, hear, speak, and act concurrently as well…