The following publications are possibly variants of this publication:
- Enhancing Pre-Trained Language Representations with Rich Knowledge for Machine Reading Comprehensionan Yang, Quan Wang, Jing Liu, Kai Liu, Yajuan Lyu, Hua Wu 0003, Qiaoqiao She, Sujian Li. acl 2019: 2346-2357 [doi]
- CBKI: A confidence-based knowledge integration framework for multi-choice machine reading comprehensionXianghui Meng, Yang Song 0010, Qingchun Bai, Taoyi Wang. kbs, 277:110796, October 2023. [doi]
- Multi-strategy Knowledge Distillation Based Teacher-Student Framework for Machine Reading ComprehensionXiaoyan Yu, Qingbin Liu, Shizhu He, Kang Liu 0001, Shengping Liu, Jun Zhao 0001, Yongbin Zhou. cncl 2021: 209-225 [doi]
- A Knowledge-aware Machine Reading Comprehension Framework for Dialogue Symptom DiagnosisXiongjun Zhao, Yingjie Cheng, Weiming Xiang, Xiang Wang, Lin Han, Jiandong Shang, Shaoliang Peng. bibm 2021: 1185-1190 [doi]
- A Multi-answer Multi-task Framework for Real-world Machine Reading ComprehensionJiahua Liu, Wan Wei, Maosong Sun, Hao Chen, Yantao Du, Dekang Lin. emnlp 2018: 2109-2118 [doi]
- Hierarchical Answer Selection Framework for Multi-passage Machine Reading ComprehensionZhaohui Li, Jun Xu, Yanyan Lan, Jiafeng Guo, Yue Feng, Xueqi Cheng. ccir 2018: 93-104 [doi]
- A Robust Adversarial Training Approach to Machine Reading ComprehensionKai Liu 0023, Xin Liu, an Yang, Jing Liu 0022, Jinsong Su, Sujian Li, Qiaoqiao She. AAAI 2020: 8392-8400 [doi]