activity
20202022
most citedEQG-RACE: Examination-Type Question Generation

6 citations · 13 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL20222 cited

Enhancing Pre-trained Models with Text Structure Knowledge for Question Generation

Zichen Wu, Xin Jia, Fanyi Qu +1

Today the pre-trained language models achieve great success for question generation (QG) task and significantly outperform traditional sequence-to-sequence approaches. However, the…

cs.CL20212 cited

Asking Questions Like Educational Experts: Automatically Generating Question-Answer Pairs on Real-World Examination Data

Fanyi Qu, Xin Jia, Yunfang Wu

Generating high quality question-answer pairs is a hard but meaningful task. Although previous works have achieved great results on answer-aware question generation, it is difficul…

cs.CL20213 cited

Enhancing Question Generation with Commonsense Knowledge

Xin Jia, Hao Wang, Dawei Yin +1

Question generation (QG) is to generate natural and grammatical questions that can be answered by a specific answer for a given context. Previous sequence-to-sequence models suffer…

physics.atom-ph2021

Temporal characterization of electron dynamics in attosecond XUV and infrared laser fields

L. Guo, Y. Jia, M. Q. Liu +5

We use a Wigner distribution-like function based on the strong field approximation theory to obtain the time-energy distributions and the ionization time distributions of electrons…

cs.CL20206 cited

EQG-RACE: Examination-Type Question Generation

Xin Jia, Wenjie Zhou, Xu Sun +1

Question Generation (QG) is an essential component of the automatic intelligent tutoring systems, which aims to generate high-quality questions for facilitating the reading practic…