AI RESEARCH
DTBench: A Synthetic Benchmark for Document-to-Table Extraction
arXiv CS.AI
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ArXi:2602.13812v3 Announce Type: replace-cross Document-to-table (Doc2Table) extraction derives structured tables from unstructured documents under a target schema, enabling reliable and verifiable SQL-based data analytics. Although large language models (LLMs) have shown promise in flexible information extraction, their ability to produce precisely structured tables remains insufficiently understood, particularly for indirect extraction that requires complex capabilities such as reasoning and conflict resolution.