AI RESEARCH
RemoteAgent: Bridging Vague Human Intents and Earth Observation with RL-based Agentic MLLMs
arXiv CS.CV
•
ArXi:2604.07765v1 Announce Type: new Earth Observation (EO) systems are essentially designed to domain experts who often express their requirements through vague natural language rather than precise, machine-friendly instructions. Depending on the specific application scenario, these vague queries can demand vastly different levels of visual precision. Consequently, a practical EO AI system must bridge the gap between ambiguous human queries and the appropriate multi-granularity visual analysis tasks, ranging from holistic image interpretation to fine-grained pixel-wise predictions.