✨TabDSR: Decompose, Sanitize, and Reason for Complex Numerical Reasoning in Tabular Data

📝 Summary:
TabDSR improves LLM performance on complex tabular numerical reasoning by decomposing queries, sanitizing tables, and using program-of-thoughts reasoning. It achieves state-of-the-art accuracy, consistently outperforming existing methods.

🔹 Publication Date: Published on Nov 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02219
• PDF: https://arxiv.org/pdf/2511.02219

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#LLM #TabularData #NumericalReasoning #DataScience #AI

✨TabTune: A Unified Library for Inference and Fine-Tuning Tabular Foundation Models

📝 Summary:
TabTune is a unified library that standardizes the workflow for tabular foundation models. It provides consistent access to state-of-the-art models, diverse adaptation strategies, and integrated evaluation for performance, calibration, and fairness.

🔹 Publication Date: Published on Nov 4

🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02802
• PDF: https://arxiv.org/pdf/2511.02802
• Github: https://github.com/Lexsi-Labs/TabTune

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For more data science resources:
✓ https://t.iss.one/DataScienceT

#TabularData #FoundationModels #MachineLearning #DataScience #AIResearch