SOURCE-LINKED INTELLIGENCE
Time-Aware Assistive Navigation
Can interactive vision-and-language agents learn not just what to say but also \textbf{\textit{when}} to say it? Current language models rarely plan over whether and when to realize a real-time response to a user. However, providing accurate and timely support for human decision-making, such as when guiding visually impaired individuals through urban environments, requires careful real-time responsiveness--poorly timed responses can distract users or add unnecessary cognitive load. As a machine intelligence challenge for Multimodal Large Language Model (MLLM)-based agents, we introduce a large
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-04T17:59:47.000Z
First collected: 2026-09-20T21:52:07.471Z. This is not the publication date.