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
StreamFlow is introduced, an efficient visual memory framework that enables dynamic, on-demand access to historical visual information and improves the visual attention score while reducing end-to-end latency and peak memory, enabling more visually grounded and efficient reasoning.
Muxin Fu, Yifan Zhang, Wentao Zhang et al.· 0 citations
To the authors' knowledge, JIT-Agent is the first model purpose-built for just-in-time harness generation, establishing harness intelligence as a trainable, transferable, and compounding dimension of agent capability orthogonal to model scaling.
Guibin Zhang, Leo Lu, Fang-Zhou Xie et al.· 0 citations
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