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MFORT-QA: Multi-hop Few-shot Open Rich Table Question Answering
March 29, 2024, 4:47 a.m. | Che Guan, Mengyu Huang, Peng Zhang
cs.CL updates on arXiv.org arxiv.org
Abstract: In today's fast-paced industry, professionals face the challenge of summarizing a large number of documents and extracting vital information from them on a daily basis. These metrics are frequently hidden away in tables and/or their nested hyperlinks. To address this challenge, the approach of Table Question Answering (QA) has been developed to extract the relevant information. However, traditional Table QA training tasks that provide a table and an answer(s) from a gold cell coordinate(s) for …
abstract arxiv challenge cs.ai cs.cl daily documents face few-shot hidden industry information metrics professionals question question answering summarizing table tables them type vital
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