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Amazon researchers propose GraphEval, a framework using knowledge graphs to detect hallucinations in LLM outputs. GraphEval applies a two-stage evaluation process that emphasizes explainability, pinpointing where hallucinations occur. A simulated code example demonstrates how NLI models flag factually inconsistent triples.
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