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ORCIDWorkshop on Machine Reading for Question Answering@ACL 2018: Melbourne, Australia
- Eunsol Choi, Minjoon Seo, Danqi Chen, Robin Jia, Jonathan Berant:
Proceedings of the Workshop on Machine Reading for Question Answering@ACL 2018, Melbourne, Australia, July 19, 2018. Association for Computational Linguistics 2018, ISBN 978-1-948087-39-1 - Yichen Gong, Samuel R. Bowman:
Ruminating Reader: Reasoning with Gated Multi-hop Attention. 1-11 - Marc-Antoine Rondeau, Timothy J. Hazen:
Systematic Error Analysis of the Stanford Question Answering Dataset. 12-20 - Seunghak Yu, Sathish Reddy Indurthi, Seohyun Back, Haejun Lee:
A Multi-Stage Memory Augmented Neural Network for Machine Reading Comprehension. 21-30 - Yuanhang Ren, Ye Du, Di Wang:
Tackling Adversarial Examples in QA via Answer Sentence Selection. 31-36 - Wei He, Kai Liu, Jing Liu, Yajuan Lyu, Shiqi Zhao, Xinyan Xiao, Yuan Liu, Yizhong Wang, Hua Wu, Qiaoqiao She, Xuan Liu, Tian Wu, Haifeng Wang:
DuReader: a Chinese Machine Reading Comprehension Dataset from Real-world Applications. 37-46 - Jörg Franke, Jan Niehues
, Alex Waibel:
Robust and Scalable Differentiable Neural Computer for Question Answering. 47-59 - Michael Boratko, Harshit Padigela, Divyendra Mikkilineni, Pritish Yuvraj, Rajarshi Das, Andrew McCallum, Maria Chang, Achille Fokoue-Nkoutche, Pavan Kapanipathi, Nicholas Mattei, Ryan Musa, Kartik Talamadupula, Michael Witbrock:
A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset. 60-70 - Yan Shvartzshanider, Ananth Balashankar, Thomas Wies, Lakshminarayanan Subramanian:
RECIPE: Applying Open Domain Question Answering to Privacy Policies. 71-77 - Sandeep Subramanian, Tong Wang, Xingdi Yuan, Saizheng Zhang, Adam Trischler, Yoshua Bengio:
Neural Models for Key Phrase Extraction and Question Generation. 78-88 - Soumya Wadhwa, Khyathi Raghavi Chandu, Eric Nyberg:
Comparative Analysis of Neural QA models on SQuAD. 89-97 - An Yang, Kai Liu, Jing Liu, Yajuan Lyu, Sujian Li:
Adaptations of ROUGE and BLEU to Better Evaluate Machine Reading Comprehension Task. 98-104
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