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Comparing Attention-Based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading Comprehension

M. Blohm, G. Jagfeld, E. Sood, X. Yu, and N. Vu. Proc. ACL SIGNLL Conference on Computational Natural Language Learning (CoNLL), page 108--118. Association for Computational Linguistics, (2018)
DOI: 10.18653/v1/K18-1011

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On Search Powered Navigation.M. Dehghani, G. Jagfeld, H. Azarbonyad, A. Olieman, J. Kamps, and M. Marx. ICTIR, page 317-320. ACM, (2017)Increasing Altruistic and Cooperative Behaviour With Simple Moral NudgesV. Capraro, G. Jagfeld, R. Klein, M. Mul, and I. van de Pol. Scientific Reports, (2019)A Computational Linguistic Study of Personal Recovery in Bipolar Disorder.G. Jagfeld. ACL (2), page 17-26. Association for Computational Linguistics, (2019)Towards a Better Semantic Role Labeling of Complex Predicates.G. Jagfeld, and L. van der Plas. HLT-NAACL, page 33-39. The Association for Computational Linguistics, (2015)Sequence-to-Sequence Models for Data-to-Text Natural Language Generation: Word- vs. Character-based Processing and Output Diversity.G. Jagfeld, S. Jenne, and N. Vu. INLG, page 221-232. Association for Computational Linguistics, (2018)Evaluating Compound Splitters Extrinsically with Textual Entailment.G. Jagfeld, P. Ziering, and L. van der Plas. ACL (2), page 58-63. Association for Computational Linguistics, (2017)Telling How to Narrow it Down: Browsing Path Recommendation for Exploratory Search.M. Dehghani, G. Jagfeld, H. Azarbonyad, A. Olieman, J. Kamps, and M. Marx. CHIIR, page 369-372. ACM, (2017)Encoding Word Confusion Networks with Recurrent Neural Networks for Dialog State Tracking.G. Jagfeld, and N. Vu. SCNLP@EMNLP 2017, page 10-17. Association for Computational Linguistics, (2017)Comparing Attention-Based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading ComprehensionM. Blohm, G. Jagfeld, E. Sood, X. Yu, and N. Vu. Proc. ACL SIGNLL Conference on Computational Natural Language Learning (CoNLL), page 108--118. Association for Computational Linguistics, (2018)

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Comparing Attention-Based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading Comprehension

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Comparing Attention-Based Convolutional and Recurrent Neural Networks: Success and Limitations in Machine Reading Comprehension