Papers with Data preparation

2 papers
Empowering Tabular Data Preparation with Language Models: Why and How? (2026.acl-long)

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Challenge: Tabular data preparation is a critical step in enhancing the usability of tabular data.
Approach: They analyze how LMs can be combined with other components for different tabular data preparation tasks.
Outcome: The proposed methods lack the ability to capture the relationships within tables and adapt to the tasks involved.
Retrieval-Based Transformer for Table Augmentation (2023.findings-acl)

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Challenge: Data preparation is one of the most expensive and time-consuming steps when performing analytics or building machine learning models.
Approach: They propose a retrieval augmented transformer model that is self-trained for table augmentation tasks.
Outcome: The proposed model outperforms current state-of-the-art models on EntiTables and WebTables.

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