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M-Plan is proposed, a closed-loop MAS framework that integrates long-term and short-term memory that enhances agents' performance on multi-turn tasks while maintaining a plug-and-play design and outperforms multiple baseline methods in both accuracy and efficiency.
LLM-based multi-agent systems (MAS) have demonstrated strong capabilities in solving complex problems across diverse domains. Recently, the dynamic orchestration of agent systems has become an important research direction. However, existing methods suffer from limited composition, misaligned dependencies, and inflexibl...
By systematically revealing the strengths and limitations of existing models in aerial-ground collaborative reasoning, AeroGround provides a foundation for developing more capable aerial-ground collaborative embodied intelligence systems.
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