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Treating negative samples differently based on their similarity to positives leads to a 13.1% boost in retrieval performance on complex queries.
LLaVA-OV-2's codec-stream tokenization lets it crush existing video-language models, especially in tasks requiring fine-grained temporal understanding of high-frequency motion.
OmniJigsaw reveals a "bi-modal shortcut phenomenon" in joint audio-visual integration, demonstrating that naive fusion can be surprisingly ineffective and highlighting the importance of carefully designed cross-modal training strategies.