no code implementations • COLING 2022 • Zichen Wu, Xin Jia, Fanyi Qu, Yunfang Wu
Specially, we present localness modeling with a Gaussian bias to enable the model to focus on answer-surrounded context, and propose a mask attention mechanism to make the syntactic structure of input passage accessible in question generation process.
Ranked #5 on Question Generation on SQuAD1.1
no code implementations • EMNLP 2021 • Fanyi Qu, Xin Jia, Yunfang Wu
This paper for the first time addresses the question-answer pair generation task on the real-world examination data, and proposes a new unified framework on RACE.
no code implementations • CCL 2021 • Xin Jia, Hao Wang, Dawei Yin, Yunfang Wu
Question generation (QG) is to generate natural and grammatical questions that can be answered by a specific answer for a given context.
1 code implementation • 11 Dec 2020 • Xin Jia, Wenjie Zhou, Xu sun, Yunfang Wu
Question Generation (QG) is an essential component of the automatic intelligent tutoring systems, which aims to generate high-quality questions for facilitating the reading practice and assessments.
no code implementations • ACL 2020 • Xin Jia, Wenjie Zhou, Xu sun, Yunfang Wu
Given a sentence and its relevant answer, how to ask good questions is a challenging task, which has many real applications.