A Survey of Automatic Hallucination Evaluation on Natural Language Generation
Published in arXiv preprint, 2024
This comprehensive survey provides an overview of automatic hallucination evaluation methods in natural language generation. We review existing approaches, categorize evaluation techniques, and identify challenges and future directions in hallucination detection and evaluation.
The survey covers various aspects including evaluation metrics, datasets, and methodologies for detecting and quantifying hallucination in different NLP tasks such as summarization, question answering, and text generation.
Recommended citation: S Qi, L Gui, Y He, Z Yuan. (2024). "A Survey of Automatic Hallucination Evaluation on Natural Language Generation." arXiv preprint arXiv:2404.12041.
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