SOURCE-LINKED INTELLIGENCE
Talk2Escape: Conversational Grounding for Vision-and-Language Navigation
While Vision-and-Language Navigation (VLN) has demonstrated remarkable success, the prevailing single-turn paradigm exposes a fundamental vulnerability: agents operate in a strictly open-loop manner. In practice, factors such as perceptual aliasing, sensor noise, and odometry drift can cause minor deviations to accumulate over time, often leading to catastrophic mission failures with no built-in mechanism for error recovery. To address this, we introduce \textit{Talk2Escape}, a proactive and model-agnostic dialogue intervention framework that reframes navigation as a closed-loop interactive pr
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-23T15:41:54.000Z
First collected: 2026-09-24T08:22:30.429Z. This is not the publication date.