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SAMOSA makes SAM-based tracking robust to complex, nonlinear motion by explicitly modeling target dynamics and enforcing geometric and semantic consistency across frames.
VLN agents can now navigate more effectively by reasoning about their own state and task progress, closing the gap between end-to-end VLMs and explicit scene mapping.
