
Large language models (LLMs) demonstrate significant potential in revolutionizing data preprocessing tasks for data mining and analytics, exhibiting high accuracy in error detection, data imputation, schema matching, and entity matching, but require further development to overcome limitations in domain specificity, computational expense, and occasional factual inaccuracies.


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leveraging-large-language-models-for-enhanced-data-preprocessing-a-comprehensive-analysis-of-capabilities-limitations-and-future-directions


Leveraging Large Language Models for Enhanced Data Preprocessing: A Comprehensive Analysis of Capabilities, Limitations, and Future Directions


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Instruction-tuned LLMs like Jellyfish enhance DP performance and generalizability.


utilizing-large-language-models-for-data-preprocessing-the-jellyfish-approach


Utilizing Large Language Models for Data Preprocessing: The Jellyfish Approach
