Papers with Unsupervised hallucination detection

1 papers
Unsupervised Hallucination Detection by Inspecting Reasoning Processes (2025.emnlp-main)

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Challenge: Unsupervised hallucination detection aims to identify hallucines generated by large language models without relying on labeled data.
Approach: They propose an unsupervised method to detect hallucinated content by large language models . they use internal representations intrinsic to factual correctness to prompt the model to verify the truthfulness of a given statement .
Outcome: The proposed framework outperforms existing unsupervised methods and is fully unsupervised and low cost.

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