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Groupwise Reward Geometry Conditioning (GRGC) is proposed, a two-stage framework that improves advantage construction by shaping student-side reward groups during both critic training and policy optimization, and introduces negligible overhead over GAD.
DiffWAM is presented, a geometry-conditioned navigation world-action model that directly transforms multi-level predictive features into continuous camera trajectories, providing a direct alternative to generate-then-reconstruct navigation pipelines.
NavGen is introduced, a text-to-video data generation pipeline that produces diverse vision-language navigation episodes across indoor and outdoor scenes and a style-diversification method that scales up long-tail data that is difficult and costly to collect.
How to endow aerial robots with the ability to operate in close proximity remains an open problem. The core challenges lie in the propulsion system’s dual-task requirement: generating manipulation forces while simultaneously counter-acting gravity. These competing demands create dynamic coupling effects during physical...
A framework that combines decentralized asynchronous reasoning, lightweight information sharing, capability aware collaboration, and a unified action interface is proposed, enabling general purpose VLMs to generate robot specific actions executed by learning free experts without task or robot specific training.
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