DreamFly: Causal Memory and Receding-Horizon Diffusion Planning for Aerial Vision-Language Navigation
Aerial vision-language navigation (VLN) requires an embodied agent to integrate visual evidence over time, plan future actions, and determine when it has reached a navigation goal under partial observability. Although recent VLA models offer a promising perception-to-action paradigm, adapting them to aerial navigation remains challenging due to limited historical context, short planning horizons, and unreliable implicit termination. To address these challenges, we propose DreamFly, a diffusion-b
Record details
Published: 12 August 2026
Source: arXiv
Category: Research
Topics: Agents & autonomy
Retrieved: 13 August 2026
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ethics.ai (12 August 2026), “DreamFly: Causal Memory and Receding-Horizon Diffusion Planning for Aerial Vision-Language Navigation,” evidence record 18774, https://ethics.ai/record/18774 (originally published by arXiv).
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