TABARD: A Novel Benchmark for Tabular Anomaly Analysis, Reasoning and Detection (2025.findings-emnlp)
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Manan Roy Choudhury, Anirudh Iyengar Kaniyar Narayana Iyengar, Shikhhar Siingh, Sugeeth Puranam, Vivek Gupta
| Challenge: | a new benchmark is constructed to evaluate the accuracy of large language models for tabular data . the benchmark uses direct, indirect, and Chain-of-Thought prompting . |
| Approach: | They propose a framework that uses prompting, self-verification and constraint-based rule execution to improve accuracy. |
| Outcome: | The proposed framework significantly improves accuracy and recall in tabular data. |
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