LLM Agents Enhance Geospatial Data Retrieval with Safety Guardrails

Researchers have developed a new framework that uses Large Language Models (LLMs) to retrieve remote sensing data via natural language queries. This system employs three agents: a Guardrail agent for safety, a General-QA agent for understanding user intent, and a Recommender-Analyst agent for generating API calls. Preliminary testing in adversarial scenarios indicated that while prompt-level safety measures enhance robustness, persistent failures in API manipulation highlight the need for more advanced, system-level defenses. AI

IMPACT This framework could streamline access to critical geospatial data for environmental monitoring and disaster response.

RANK_REASON The cluster contains a research paper published on arXiv detailing a new LLM framework. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• alphaXiv
• arXiv
• CatalyzeX
• CORE Recommender
• DagsHub
• General-QA
• Gotit.pub
• Hugging Face
• Influence Flower
• Recommender-Analyst
• ScienceCast

• paper
• safety
• infra

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