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Hybrid Multi-Agent Systems for Auditable AI Surveying

2025-11-18

Abstract excerpt

<title>Abstract</title> <p>Systematically acquiring expert knowledge remains a bottleneck. Large Language Models (LLMs) scale interaction but introduce a governance challenge: inconsistent coverage, topic drift, and user steering. We present MHAESTRO, a hybrid two-phase approach that aims for both scale and accountable control. In Phase 1, a Knowledge-Engineering tool K-Eng compiles expert input into a versioned...

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Literature Corpus work: cc5427c6-ef9b-577d-9798-c6ccad9297e8
DOI: 10.21203/rs.3.rs-8105108/v1

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