暂无分享,去创建一个
Jungang Xu | Yingfei Sun | Xu Chen | Boyu Qiu | Yingfei Sun | Boyu Qiu | Jungang Xu | Xu Chen
[1] Danqi Chen,et al. A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task , 2016, ACL.
[2] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[3] Deng Cai,et al. MEMEN: Multi-layer Embedding with Memory Networks for Machine Comprehension , 2017, ArXiv.
[4] Shuohang Wang,et al. Machine Comprehension Using Match-LSTM and Answer Pointer , 2016, ICLR.
[5] Jian Zhang,et al. SQuAD: 100,000+ Questions for Machine Comprehension of Text , 2016, EMNLP.
[6] Ming Zhou,et al. Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base , 2018, NeurIPS.
[7] Eunsol Choi,et al. TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension , 2017, ACL.
[8] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[9] Jason Weston,et al. The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations , 2015, ICLR.
[10] Richard Socher,et al. Dynamic Coattention Networks For Question Answering , 2016, ICLR.
[11] Percy Liang,et al. Know What You Don’t Know: Unanswerable Questions for SQuAD , 2018, ACL.
[12] Chris Dyer,et al. The NarrativeQA Reading Comprehension Challenge , 2017, TACL.
[13] Jianfeng Gao,et al. A Human Generated MAchine Reading COmprehension Dataset , 2018 .
[14] Percy Liang,et al. Adversarial Examples for Evaluating Reading Comprehension Systems , 2017, EMNLP.
[15] Yelong Shen,et al. ReasoNet: Learning to Stop Reading in Machine Comprehension , 2016, CoCo@NIPS.
[16] Ming-Wei Chang,et al. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , 2019, NAACL.
[17] Ming Zhou,et al. Reinforced Mnemonic Reader for Machine Reading Comprehension , 2017, IJCAI.
[18] Ming Zhou,et al. Gated Self-Matching Networks for Reading Comprehension and Question Answering , 2017, ACL.
[19] Guokun Lai,et al. RACE: Large-scale ReAding Comprehension Dataset From Examinations , 2017, EMNLP.
[20] Kentaro Inui,et al. What Makes Reading Comprehension Questions Easier? , 2018, EMNLP.
[21] Matthew Richardson,et al. MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text , 2013, EMNLP.
[22] Dirk Weissenborn,et al. Making Neural QA as Simple as Possible but not Simpler , 2017, CoNLL.
[23] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[24] Danqi Chen,et al. CoQA: A Conversational Question Answering Challenge , 2018, TACL.
[25] Jeffrey Pennington,et al. GloVe: Global Vectors for Word Representation , 2014, EMNLP.
[26] Luke S. Zettlemoyer,et al. Deep Contextualized Word Representations , 2018, NAACL.
[27] Xinyan Xiao,et al. DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications , 2017, QA@ACL.