BriefGPT.xyz
Apr, 2020
通过文本生成解释问答模型
Explaining Question Answering Models through Text Generation
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Veronica Latcinnik, Jonathan Berant
TL;DR
本论文提出了一种模型,通过生成文本提供细节信息,使多选题回答模型更容易理解,并采用多种损失函数来鼓励自然文本输出,从而达到与端到端架构相当的性能水平。
Abstract
Large
pre-trained language models
(LMs) have been shown to perform surprisingly well when fine-tuned on tasks that require commonsense and world knowledge. However, in
end-to-end architectures
, it is difficult to
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