AI RESEARCH
AURA: Always-On Understanding and Real-Time Assistance via Video Streams
arXiv CS.CV
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ArXi:2604.04184v1 Announce Type: new Video Large Language Models (VideoLLMs) have achieved strong performance on many video understanding tasks, but most existing systems remain offline and are not well-suited for live video streams that require continuous observation and timely response. Recent streaming VideoLLMs have made progress, yet current approaches often rely on decoupled trigger-response pipelines or are limited to captioning-style narration, reducing their effectiveness for open-ended question answering and long-horizon interaction.