HearthNet is an edge multi-agent orchestration system that runs role-specialized LLM agents locally to handle natural-language smart-home control, conflict resolution, and failure recovery through MQTT and shared state.
Sentinel Agents for Secure and Trustworthy Agentic AI in Multi-Agent Systems
5 Pith papers cite this work. Polarity classification is still indexing.
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No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.
A meta-cognitive agentic framework coordinates specialized cybersecurity agents through a judgment mechanism to improve decision quality under uncertainty and noise on standard benchmarks.
MADP multi-agent pipeline with human-in-the-loop achieves 97% full automation on 955 real documents, 98.5% accuracy on ablation set, and 69-70% reductions in FTE, energy, and emissions versus manual processing.
A rapid review of fairness in LLM-enabled multi-agent systems for the software development lifecycle concludes that the field lacks standardized evaluations, broad coverage, and effective governance, leaving it unprepared for deployable fair systems.
citing papers explorer
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HearthNet: Edge Multi-Agent Orchestration for Smart Homes
HearthNet is an edge multi-agent orchestration system that runs role-specialized LLM agents locally to handle natural-language smart-home control, conflict resolution, and failure recovery through MQTT and shared state.
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Security Considerations for Multi-agent Systems
No existing AI security framework covers a majority of the 193 identified multi-agent system threats in any category, with OWASP Agentic Security Initiative achieving the highest overall coverage at 65.3%.
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Agentic AI for Cybersecurity: A Meta-Cognitive Architecture for Governable Autonomy
A meta-cognitive agentic framework coordinates specialized cybersecurity agents through a judgment mechanism to improve decision quality under uncertainty and noise on standard benchmarks.
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MADP: A Multi-Agent Pipeline for Sustainable Document Processing with Human-in-the-Loop
MADP multi-agent pipeline with human-in-the-loop achieves 97% full automation on 955 real documents, 98.5% accuracy on ablation set, and 69-70% reductions in FTE, energy, and emissions versus manual processing.
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Fairness in Multi-Agent Systems for Software Engineering: An SDLC-Oriented Rapid Review
A rapid review of fairness in LLM-enabled multi-agent systems for the software development lifecycle concludes that the field lacks standardized evaluations, broad coverage, and effective governance, leaving it unprepared for deployable fair systems.