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This work introduces a spatial-semantic uncertainty formulation that maintains separate beliefs over each component and integrates probabilistic VLM evidence into a global target-identity posterior, including probability mass for undiscovered targets.
Tracking accuracy in multi-robot systems can be fundamentally limited by the geometry of information transport, leading to diminishing returns on communication improvements.
