Papers by Akshar Kaul
Quality Assessment of Tabular Data using Large Language Models and Code Generation (2025.emnlp-industry)
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| Challenge: | Data quality is vital for business decisions; poor data quality costs organizations an average of $12.9 million annually. |
| Approach: | They propose a framework that combines statistical inliner detection with LLM-driven rule and code generation. |
| Outcome: | The proposed framework produces semantically valid quality rules and validates them with retrieval-augmented generation (RAG) Extensive evaluations on benchmark datasets confirm the effectiveness of the proposed framework. |