Minos uses a two-tiered multi-agent architecture with retrieval-augmented reasoning and FSM-coordinated agents to reconstruct attack scenarios from provenance data, reporting 0.92 recall and 0.64 precision on 14 scenarios.
In: Proceedings of the 36th annual acm symposium on user interface software and technology
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
BrainMem equips LLM-based embodied planners with working, episodic, and semantic memory that evolves interaction histories into retrievable knowledge graphs and guidelines, raising success rates on long-horizon 3D benchmarks.
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Minos: A Multi-Agent Collaborative Framework for Provenance-Based Backward Tracking
Minos uses a two-tiered multi-agent architecture with retrieval-augmented reasoning and FSM-coordinated agents to reconstruct attack scenarios from provenance data, reporting 0.92 recall and 0.64 precision on 14 scenarios.
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BrainMem: Brain-Inspired Evolving Memory for Embodied Agent Task Planning
BrainMem equips LLM-based embodied planners with working, episodic, and semantic memory that evolves interaction histories into retrievable knowledge graphs and guidelines, raising success rates on long-horizon 3D benchmarks.