Single-cell foundation models (scFMs) are transforming computational biology by enabling generalizable, task-agnostic representations for versatile single-cell analysis. Despite their progress in facilitating rapid deployment for downstream tasks, off-the-shelf scFMs still have some overlooked concerns: (I) (Pretrainin...
Tian-Yu Liu, Fan Zhang, Jia-Yuan Chen et al.· 0 citations
Video understanding is a fundamental task for evaluating the capabilities of multimodal large language models (MLLMs). However, existing leading models have already achieved approximately 90% accuracy on the Video-MME leaderboard, suggesting that conventional single-turn video understanding tasks are becoming increasin...
Fan Zhang, Guang-Ming Yao, Jin-Yang Wu et al.· 0 citations
Streaming video understanding requires multimodal large language models (MLLMs) to process continuous visual inputs and respond to user queries under strict causality and bounded memory. Existing approaches typically compress historical observations into an external memory bank and retrieve query-relevant evidence as a...
Hongyu Qu, Guang-Ming Yao, Ling Xing et al.· 0 citations
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