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2nd MRQA@EMNLP 2019: Hong Kong, China
- Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, Danqi Chen:
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, MRQA@EMNLP 2019, Hong Kong, China, November 4, 2019. Association for Computational Linguistics 2019, ISBN 978-1-950737-81-9 - Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, Danqi Chen:
MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension. 1-13 - Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Lei Cui, Songhao Piao, Ming Zhou:
Inspecting Unification of Encoding and Matching with Transformer: A Case Study of Machine Reading Comprehension. 14-18 - Frédéric Béchet, Cindy Aloui, Delphine Charlet, Géraldine Damnati, Johannes Heinecke, Alexis Nasr, Frédéric Herledan:
CALOR-QUEST : generating a training corpus for Machine Reading Comprehension models from shallow semantic annotations. 19-26 - Xiaoman Pan, Kai Sun, Dian Yu, Jianshu Chen, Heng Ji, Claire Cardie, Dong Yu:
Improving Question Answering with External Knowledge. 27-37 - Qian Li, Hui Su, Cheng Niu, Daling Wang, Zekang Li, Shi Feng, Yifei Zhang:
Answer-Supervised Question Reformulation for Enhancing Conversational Machine Comprehension. 38-47 - Wenhan Xiong, Mo Yu, Xiaoxiao Guo, Hong Wang, Shiyu Chang, Murray Campbell, William Yang Wang:
Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering. 48-52 - Bowen Wu, Haoyang Huang, Zongsheng Wang, Qihang Feng, Jingsong Yu, Baoxun Wang
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Improving the Robustness of Deep Reading Comprehension Models by Leveraging Syntax Prior. 53-57 - Kevin Lin, Oyvind Tafjord, Peter Clark, Matt Gardner:
Reasoning Over Paragraph Effects in Situations. 58-62 - Mao Nakanishi, Tetsunori Kobayashi, Yoshihiko Hayashi:
Towards Answer-unaware Conversational Question Generation. 63-71 - Elozino Egonmwan, Vittorio Castelli, Md. Arafat Sultan:
Cross-Task Knowledge Transfer for Query-Based Text Summarization. 72-77 - Stefanos Angelidis
Book QA: Stories of Challenges and Opportunities. 78-85 - Yi-Ting Yeh, Yun-Nung Chen:
FlowDelta: Modeling Flow Information Gain in Reasoning for Conversational Machine Comprehension. 86-90 - Haoyu Wang, Mo Yu, Xiaoxiao Guo, Rajarshi Das, Wenhan Xiong, Tian Gao:
Do Multi-hop Readers Dream of Reasoning Chains? 91-97 - Norio Takahashi, Tomohide Shibata, Daisuke Kawahara, Sadao Kurohashi:
Machine Comprehension Improves Domain-Specific Japanese Predicate-Argument Structure Analysis. 98-104 - Matt Gardner, Jonathan Berant, Hannaneh Hajishirzi, Alon Talmor, Sewon Min:
On Making Reading Comprehension More Comprehensive. 105-112 - Rajarshi Das, Ameya Godbole, Dilip Kavarthapu, Zhiyu Gong, Abhishek Singhal, Mo Yu, Xiaoxiao Guo, Tian Gao, Hamed Zamani, Manzil Zaheer, Andrew McCallum:
Multi-step Entity-centric Information Retrieval for Multi-Hop Question Answering. 113-118 - Anthony Chen, Gabriel Stanovsky, Sameer Singh, Matt Gardner:
Evaluating Question Answering Evaluation. 119-124 - Hemant Pugaliya, James Route, Kaixin Ma, Yixuan Geng, Eric Nyberg:
Bend but Don't Break? Multi-Challenge Stress Test for QA Models. 125-136 - Amin Ahmad, Noah Constant, Yinfei Yang, Daniel Cer:
ReQA: An Evaluation for End-to-End Answer Retrieval Models. 137-146 - Dheeru Dua, Ananth Gottumukkala, Alon Talmor, Sameer Singh, Matt Gardner:
Comprehensive Multi-Dataset Evaluation of Reading Comprehension. 147-153 - Ying-Hong Chan, Yao-Chung Fan:
A Recurrent BERT-based Model for Question Generation. 154-162 - Junmo Kang, Haritz Puerto San Roman, Sung-Hyon Myaeng:
Let Me Know What to Ask: Interrogative-Word-Aware Question Generation. 163-171 - Lea Frermann:
Extractive NarrativeQA with Heuristic Pre-Training. 172-182 - Takumi Takahashi, Motoki Taniguchi, Tomoki Taniguchi, Tomoko Ohkuma:
CLER: Cross-task Learning with Expert Representation to Generalize Reading and Understanding. 183-190 - Reham A. Osama, Nagwa M. El-Makky, Marwan Torki:
Question Answering Using Hierarchical Attention on Top of BERT Features. 191-195 - Seanie Lee, Donggyu Kim, Jangwon Park:
Domain-agnostic Question-Answering with Adversarial Training. 196-202 - Dan Su
Generalizing Question Answering System with Pre-trained Language Model Fine-tuning. 203-211 - Hongyu Li
D-NET: A Pre-Training and Fine-Tuning Framework for Improving the Generalization of Machine Reading Comprehension. 212-219 - Shayne Longpre, Yi Lu, Zhucheng Tu, Chris DuBois:
An Exploration of Data Augmentation and Sampling Techniques for Domain-Agnostic Question Answering. 220-227
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