CuraView detects sentence-level faithfulness hallucinations in medical discharge summaries via GraphRAG knowledge graphs and multi-agent evidence grading, achieving 0.831 F1 on critical contradictions with a fine-tuned Qwen3-14B model and 50% relative improvement over baselines.
Medical Graph RAG : Evidence-based Medical Large Language Model via Graph Retrieval-Augmented Generation
4 Pith papers cite this work, alongside 50 external citations. Polarity classification is still indexing.
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A hybrid graph-text retrieval system for cyber threat intelligence improves multi-hop question answering by up to 35% over vector-based RAG on a 3,300-question benchmark.
Quantum Knowledge Graphs model context-dependent triplet validity and improve LLM medical reasoning accuracy by 1.4 to 6 percentage points over baselines.
citing papers explorer
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CuraView: A Multi-Agent Framework for Medical Hallucination Detection with GraphRAG-Enhanced Knowledge Verification
CuraView detects sentence-level faithfulness hallucinations in medical discharge summaries via GraphRAG knowledge graphs and multi-agent evidence grading, achieving 0.831 F1 on critical contradictions with a fine-tuned Qwen3-14B model and 50% relative improvement over baselines.
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Beyond RAG for Cyber Threat Intelligence: A Systematic Evaluation of Graph-Based and Agentic Retrieval
A hybrid graph-text retrieval system for cyber threat intelligence improves multi-hop question answering by up to 35% over vector-based RAG on a 3,300-question benchmark.
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Quantum Knowledge Graph: Modeling Context-Dependent Triplet Validity
Quantum Knowledge Graphs model context-dependent triplet validity and improve LLM medical reasoning accuracy by 1.4 to 6 percentage points over baselines.
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