Papers by Fengchang Yu
TabDSR: Decompose, Sanitize, and Reason for Complex Numerical Reasoning in Tabular Data (2025.findings-emnlp)
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| Challenge: | Large language models often underperform due to complex queries, noisy data, and limited numerical capabilities. |
| Approach: | They propose a framework that integrates seamlessly with mainstream LLMs to improve tabular reasoning. |
| Outcome: | The proposed framework outperforms existing methods in state-of-the-art analysis. |