Stochastic Answer Networks for SQuAD 2.0
2018-09-24Code Available0· sign in to hype
Xiaodong Liu, Wei Li, Yuwei Fang, Aerin Kim, Kevin Duh, Jianfeng Gao
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- github.com/kevinduh/san_mrcOfficialIn paperpytorch★ 0
- github.com/lduml/blogtf★ 0
- github.com/Xaniar87/SAN_SQuAD2pytorch★ 0
- github.com/yongbowin/san_mrc_annotationpytorch★ 0
- github.com/aerinkim/squad_2018pytorch★ 0
Abstract
This paper presents an extension of the Stochastic Answer Network (SAN), one of the state-of-the-art machine reading comprehension models, to be able to judge whether a question is unanswerable or not. The extended SAN contains two components: a span detector and a binary classifier for judging whether the question is unanswerable, and both components are jointly optimized. Experiments show that SAN achieves the results competitive to the state-of-the-art on Stanford Question Answering Dataset (SQuAD) 2.0. To facilitate the research on this field, we release our code: https://github.com/kevinduh/san_mrc.