Instruction-guided video editing has made significant progress, yet existing methods use multimodal large language models (MLLMs) primarily as semantic encoders, so they often fall short in working with implicit edits that require causal or semantic reasoning. To bridge this fundamental gap in video editing, we propose...
Dong-Hao Zhou, Hao-Yang He, Fan Zhang et al.· 0 citations
MOTIVATION
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)...
Tian-Yu Liu, Fan Zhang, Jia-Yuan Chen et al.· Bioinformatics· 0 citations
This work introduces VideoGAIA, an agentic video understanding benchmark for general artificial intelligence (AI) assistants, and formulates video understanding as a multi-turn, tool-augmented interaction process, where models must iteratively perceive videos, invoke external tools, gather complementary information, an...
Fan Zhang, Guang-Ming Yao, Jin-Yang Wu et al.· 1 citation
This work introduces LatentStream, a progressive latent working memory framework that shifts streaming memory from store-and-retrieve to retrieve-and-internalize, and achieves new state-of-the-art results on existing online and offline video benchmarks.
Hongyu Qu, Guang-Ming Yao, Ling Xing et al.· 0 citations
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