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Jan, 2025
TableMaster:推进语言模型表格理解的秘籍
TableMaster: A Recipe to Advance Table Understanding with Language Models
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TL;DR
本研究针对当前语言模型在表格理解方面的不足,提出了TableMaster这一框架,解决了目标数据定位、表格语义缺失、文本推理中的数值不准确及符号推理的语义灵活性不足等四大挑战。研究结果表明,TableMaster在WikiTQ数据集上的准确率达到78.13%,有效提升了表格理解能力。
Abstract
Tables serve as a fundamental format for representing structured relational data. While current
Language Models
(LMs) excel at many text-based tasks, they still face challenges in
Table Understanding
due to the c
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