An Ensemble Model for Winning a Chinese Machine Reading Comprehension Competition

To facilitate the application of machine reading comprehension, the 28th Research Institute of China Electronics Technology Group Corporation organized a Chinese machine reading comprehension competition, namely the LES Cup Challenge, in October 2018. The competition introduces a big dataset of long articles and improperly labelled data, therefore challenges the state-of-the-art methods in this area. We proposed an ensemble model of four novel recurrent neural networks, which ranked on the top 2% over more than 250 teams (97 teams successfully submitted results) mainly from top universities and AI companies of China, and won the third prize (3000 USD) of the competition.

[1]  Ming Zhou,et al.  Multiway Attention Networks for Modeling Sentence Pairs , 2018, IJCAI.

[2]  Jianfeng Gao,et al.  A Human Generated MAchine Reading COmprehension Dataset , 2018 .

[3]  Jason Weston,et al.  Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks , 2015, ICLR.

[4]  Richard Socher,et al.  Efficient and Robust Question Answering from Minimal Context over Documents , 2018, ACL.

[5]  Ting Liu,et al.  Attention-over-Attention Neural Networks for Reading Comprehension , 2016, ACL.

[6]  Kai Liu,et al.  Multi-Passage Machine Reading Comprehension with Cross-Passage Answer Verification , 2018, ACL.

[7]  Jian Zhang,et al.  SQuAD: 100,000+ Questions for Machine Comprehension of Text , 2016, EMNLP.

[8]  Ming Zhou,et al.  S-Net: From Answer Extraction to Answer Generation for Machine Reading Comprehension , 2017, AAAI 2017.

[9]  Chin-Yew Lin,et al.  ROUGE: A Package for Automatic Evaluation of Summaries , 2004, ACL 2004.

[10]  Phil Blunsom,et al.  Teaching Machines to Read and Comprehend , 2015, NIPS.

[11]  Ming Zhou,et al.  Reinforced Mnemonic Reader for Machine Reading Comprehension , 2017, IJCAI.

[12]  Luke S. Zettlemoyer,et al.  Deep Contextualized Word Representations , 2018, NAACL.

[13]  Salim Roukos,et al.  Bleu: a Method for Automatic Evaluation of Machine Translation , 2002, ACL.

[14]  Ali Farhadi,et al.  Bidirectional Attention Flow for Machine Comprehension , 2016, ICLR.

[15]  Nan Yang,et al.  I Know There Is No Answer: Modeling Answer Validation for Machine Reading Comprehension , 2018, NLPCC.

[16]  Furu Wei,et al.  Read + Verify: Machine Reading Comprehension with Unanswerable Questions , 2018, AAAI.