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APT-Tune is proposed, a parameter-efficient recipe that teaches VLMs to use causal transitions without forgetting how to answer video questions, and substantially improves APT recall while also improving event-level video transfer.
VLAFP is the first deep audio fingerprinting model capable of processing audio of variable length, for both training and testing, and outperforms existing state-of-the-arts in live audio identification and audio retrieval across three real-world datasets.
Experimental results demonstrate that Phys4D substantially improves fine-grained spatiotemporal and physical consistency compared to appearance-driven baselines, while maintaining strong generative performance.
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