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arXiv — cs.AI preprintsInternational21 October 2026

DISTRACT: Degradation-Indexed Study of Textual Reference Across Competing Targets

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arXiv:2610.28419v1 Announce Type: cross Abstract: Vision-language trackers (VLTs) accept descriptions intended to assist tracking, but accepting text does not establish that its content changes tracking decisions, particularly as visual evidence deteriorates. We introduce DISTRACT, a matched-intervention benchmark that holds video, target, and distractor fixed while crossing four text priors with four image degradations along a controlled severity axis. We evaluate five VLTs on four datasets using behavioral contrasts, layerwise representation probes, and activation patching. Molmo2 and JointN
— arXiv — cs.AI preprints

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