Papers with Improving Noisy data

1 papers
FiNE: Filtering and Improving Noisy Data Elaborately with Large Language Models (2025.naacl-long)

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Challenge: Currently, there are two mainstream methods for improving data integrity: data filtering and data augmentation.
Approach: They propose a method to improve data integrity by combining data filtering and data augmentation with LLMs.
Outcome: The proposed method surpasses the open-source chat version on HalluQA by 8.45 on the open source version.

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