| ［1］ |
Rajpurkar P,Zhang J,Lopyrev K,et al.SQuAD:100,000+questions for machine comprehension of text［C］∥Proc of the 2016 Conference on Empirical Methods in Natural Language Processing,2016:2383-2392.
|
| ［2］ |
He W,Liu K,Liu J,et al.DuReader:A Chinese machine reading comprehension dataset from real-world applications［C］∥Proc of the 56th Annual Meeting of the Association for Computational Linguistics,2018:37-46.
|
| ［3］ |
Devlin J,Chang M W,Lee K,et al.BERT:Pre-training of deep bidirectional transformers for language understanding［C］∥Proc of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies,2019:4171-4186.
|
| ［4］ |
Tang H X,Liu J,Li H Y,et al.DuReaderrobust:A Chinese dataset towards evaluating the robustness of machine reading comprehension models［J］.arXiv:2004.11142,2021.
|
| ［5］ |
Cui Y M, Che W X,Liu T,et al.Pre-training with whole word masking for Chinese BERT［J］.arXiv:1906.08101,2021.
|
| ［6］ |
Rajpurkar P,Jia R,Liang P.Know what you don’t know:Unanswerable questions for SQuAD［C］∥Proc of the 56th Annual Meeting of the Association for Computational Linguistics,2018:784-789.
|
| ［7］ |
Nguyen T,Rosenberg M,Song X,et al.MS MARCO:A human generated machine reading comprehension dataset［J］.arXiv:1611.09268,2018.
|
| ［8］ |
Reddy S,Chen D Q, Manning C D.CoQA:A conversational question answering challenge［J］.arXiv:1808.07042,2019.
|
| ［9］ |
Yang Z L,Qi P,Zhang S Z,et al.Hotpot-QA:A dataset for diverse,explainable multi-hop question answering［C］∥Porc of the 2018 Conference on Empirical Methods in Natural Language Processing,2018:2369-2380.
|
| ［10］ |
Dua D,Wang Y Z,Dasigi P,et al.DROP:A reading comprehension benchmark requiring discrete reasoning over paragraphs［C］∥Proc of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies,2019:2368-2378.
|
| ［11］ |
Talmor A, Herzig J,Lourie N,et al.Commonsenseqa:A question answering challenge targeting commonsense knowledge［C］∥Proc of the 17th Annual Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies,2019:4149-4158.
|
| ［12］ |
Li Ye-qiu, Tang Hong-xuan,Qian Jin,et al.Robustness of Chinese machine reading comprehension［J］.Acta Scientiarum Naturalium Universitatis Pekinensis,2021,57(1):16-22.(in Chinese)
|
| ［13］ |
Hirschman L,Light M,Breck E,et al.Deep read:A reading comprehension system［C］∥Proc of the 37th Annual Meeting of the Association for Computational Linguistics,1999:325-333.
|
| ［14］ |
Riloff E,Thelen M.A rule-base question answering system for reading comprehension tests［C］∥Proc of the 2000 ANLP/NAACL Workshop on Reading Comprehension Evaluation for Computer-based Language Understanding Systems,2000:13-19.
|
| ［15］ |
Hermann K M,Kocisky T,Grefenstette E,et al.Teaching machines to read and comprehend［C］∥Proc of the 28th International Conference on Neural Information Processing Systems,2015:1693-1701.
|
| ［16］ |
Seo M J,Kembhavi A,Farhadi A,et al.Bidirectional attention flow for machine comprehension［J］.arXiv:1611.01603,2018.
|
| ［17］ |
Wang W H,Yang N,Wei F R,et al.Gated self-matching networks for reading comprehension and question answering［C］∥Proc of the 55th Annual Meeting of the Association for Computational Linguistics,2017:189-198.
|
| ［18］ |
Sun Y, Wang S H,Li Y K,et al.ERNIE:Enhanced representation through knowledge integration［J］.arXiv:1904.09223,2019.
|
| ［19］ |
Liu Y H,Ott M,Goyal N,et al.RoBERTa:A robustly optimized BERT pretraining approach［J］.arXiv:1907.11692,2019.
|
| ［20］ |
Lan Z Z,Chen M D,Goodman S,et al.ALBERT:A lite BERT for self-supervised learning of language representations［J］.arXiv:1909.11942,2020.
|
| ［21］ |
Xia J N, Wu C,Yan M. Incorporating relation knowledge into commonsense reading comprehensionwith multi-task learning［C］∥Proc of the 28th ACM Intrnational Conference on Information and Knowledge Management,2019:2393-2396.
|
| ［22］ |
Liu X D, He P C,Chen W Z,et al.Multi-task deep neural networks for natural language understanding［C］∥Proc of the 57th Annual Meeting of the Association for Computational Linguistics,2019:4487-4496.
|
| ［23］ |
Qian Jin, Huang Rong-tao,Zou Bo-wei,et al.Generative reading comprehension via multi-task learning［J］.Journal of Chinese Information Processing,2021,35(12):103-111.(in Chinese)
|
|
附中文参考文献：
|
| ［12］ |
李烨秋,唐竑轩,钱锦,等.中文机器阅读理解的鲁棒性研究［J］.北京大学学报(自然科学版),2021,57(1):16-22.
|
| ［23］ |
钱锦,黄荣涛,邹博伟,等.基于多任务学习的生成式阅读理解［J］.中文信息学报，2021,35(12):103-111.
|
