MaP-AVR: A Meta-Action Planner for Agents Leveraging Vision Language Models and Retrieval-Augmented Generation
Published:Dec 22, 2025 14:58
•1 min read
•ArXiv
Analysis
This article introduces MaP-AVR, a novel meta-action planner. The core idea is to combine Vision Language Models (VLMs) and Retrieval-Augmented Generation (RAG) for agent planning. The use of RAG suggests an attempt to improve the agent's ability to access and utilize external knowledge, potentially mitigating some limitations of VLMs. The title clearly indicates the focus on agent planning within the context of AI research.
Key Takeaways
Reference
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