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.
Hallucination mitigation using agentic ai natural language- based frameworks
2 Pith papers cite this work. Polarity classification is still indexing.
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In kinship-dominant agent swarms, adding logical agents increases stability of erroneous trajectories, leading to logic saturation with zero internal entropy but unit factual error.
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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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The Inverse-Wisdom Law: Architectural Tribalism and the Consensus Paradox in Agentic Swarms
In kinship-dominant agent swarms, adding logical agents increases stability of erroneous trajectories, leading to logic saturation with zero internal entropy but unit factual error.