Tag: LLM multi-agent systems
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Isolated Self-Correction Beats Peer Debate in AI Accuracy
Study reveals isolated self-correction outperforms peer debate in multi-agent AI, improving accuracy while reducing computational costs significantly.
GRAIL: Fast, Accurate Agent Discovery with SLM Indexing
Discover GRAIL, a hybrid resonance framework enabling sub-400ms real-time agent discovery with SLM-enhanced indexing for superior speed and accuracy.
EngiAgent: AI-Driven Engineering Problem Solving with Feasibility
Discover EngiAgent, a multi-agent AI system ensuring feasible solutions for complex engineering problems through coordinated LLM agents.
Belief Revision Postulates in Multi-Agent Systems Explained
Explore how belief revision postulates apply to multi-agent systems, enhancing epistemic planning and dynamic belief updates among agents.
Efficient Multi-Agent Framework for Long-Horizon Planning
Discover a novel multi-agent framework that boosts long-horizon planning efficiency by prioritizing planner roles and reinforcement learning.