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The SAC^3 method utilizes accuracy as a primary metric to evaluate the performance of hallucination detection in black-box language models, as described in [1].
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EdinburghNLP/awesome-hallucination-detection - GitHub github.com 1 fact
referenceThe SAC^3 method for reliable hallucination detection in black-box language models uses accuracy and AUROC as metrics for classification QA and open-domain QA, and utilizes datasets including Prime number and senator search from Snowball Hallucination, HotpotQA, and Nq-open QA.