Papers by Wenfa Qi

1 papers
Detecting Hallucinations in Retrieval-Augmented Generation via Semantic-level Internal Reasoning Graph (2026.findings-acl)

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Challenge: Existing methods for detecting faithfulness hallucinations are coarse or do not capture the models’ internal reasoning processes, making it difficult to learn.
Approach: They propose a semantic-level internal reasoning graph-based method for detecting faithfulness hallucination using Large language models.
Outcome: The proposed method achieves better overall performance compared to state-of-the-art baselines on RAGTruth and Dolly-15k.

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