论文标题

带有细粒捕犬的数值推理问答系统和Finqa多个发电机的合奏

A Numerical Reasoning Question Answering System with Fine-grained Retriever and the Ensemble of Multiple Generators for FinQA

论文作者

Wang, Bin, Ju, Jiangzhou, Mao, Yunlin, Dai, Xin-Yu, Huang, Shujian, Chen, Jiajun

论文摘要

金融领域中的数值推理 - 进行定量分析并总结了财务报告中的信息 - 可以大大提高业务效率并降低数十亿美元的成本。在这里,我们提出了一个数值推理问答系统,以回答财务文本和表数据源之间的数值推理问题,该问题包括回收器模块,发电机模块和集合模块。具体而言,在回猎犬模块中,除了检索整个行数据外,我们还创新了一个细胞回收器,该池回收可以检索金单元,以避免将同一行中的无关和相似的单元带到发电机模块的输入中。在发电机模块中,我们利用多个生成器来生产程序,这是回答问题的操作步骤。最后,在整体模块中,我们集成了多个程序,以选择最佳程序作为系统的输出。在FinQA竞争中的最终私人测试集中,我们的系统获得了69.79的执行精度。

The numerical reasoning in the financial domain -- performing quantitative analysis and summarizing the information from financial reports -- can greatly increase business efficiency and reduce costs of billions of dollars. Here, we propose a numerical reasoning question answering system to answer numerical reasoning questions among financial text and table data sources, consisting of a retriever module, a generator module, and an ensemble module. Specifically, in the retriever module, in addition to retrieving the whole row data, we innovatively design a cell retriever that retrieves the gold cells to avoid bringing unrelated and similar cells in the same row to the inputs of the generator module. In the generator module, we utilize multiple generators to produce programs, which are operation steps to answer the question. Finally, in the ensemble module, we integrate multiple programs to choose the best program as the output of our system. In the final private test set in FinQA Competition, our system obtains 69.79 execution accuracy.

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