LLMs offer a cost-efficient method for dataset cleansing, potentially replacing expensive human annotator processes. The study introduces an LLM-based strategy, using methods like chain-of-thought and majority voting, validating its effectiveness on the Multi-News dataset used for summarization tasks.

This innovation could herald a new era in which AI plays a central role in data quality control, allowing for more reliable and efficient model training across various AI applications.