BriefGPT.xyz
Apr, 2019
基于问答奖励的摘要生成引导
Guiding Extractive Summarization with Question-Answering Rewards
HTML
PDF
Kristjan Arumae, Fei Liu
TL;DR
本文提出了一种利用问答奖励来引导监督式摘要系统的新框架,通过人类摘要获得问答对来评估总结与原文件的关系,并且该系统学习如何推广信息量大、流畅度高且在问答方面表现良好的总结,结果表明其表现优于基线总结和人类评估。
Abstract
Highlighting while reading is a natural behavior for people to track salient content of a document. It would be desirable to teach an
extractive
summarizer
to do the same. However, a major obstacle to the develop
→