Graph-grounded optimization sources problem elements from knowledge graphs and shows Rao-family metaheuristics plus OR-tools perform differently across seven real-world KG-backed problems while surfacing data issues.
arXiv preprint arXiv:2508.02999 , year =
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A confidence-calibrated knowledge graph framework for multi-agent traceability coordination with a two-stage link prediction pipeline, seeding mechanism, and consistency protocol, evaluated on an automotive case study.
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Graph-Grounded Optimization: Rao-Family Metaheuristics, Classical OR, and SLM-Driven Formulation over Knowledge Graphs
Graph-grounded optimization sources problem elements from knowledge graphs and shows Rao-family metaheuristics plus OR-tools perform differently across seven real-world KG-backed problems while surfacing data issues.
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Trust-Aware Multi-Agent Traceability: Confidence-Calibrated Knowledge Graphs for Consistent Software Artifact Management
A confidence-calibrated knowledge graph framework for multi-agent traceability coordination with a two-stage link prediction pipeline, seeding mechanism, and consistency protocol, evaluated on an automotive case study.