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What is Hallucination Mitigation in LLMs Survey about?

This paper presents a comprehensive survey of over thirty-two techniques developed to mitigate hallucination in large language models. Notable techniques discussed include Retrieval-Augmented Generation, Knowledge Retrieval, CoNLI, and CoVe. The paper also introduces a detailed taxonomy categorizing these methods and analyzes the challenges and limitations of current approaches.

Author

julian.wang

Language

EN