机器阅读理解 - 专知荟萃

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机器阅读理解

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包括微软、CMU、Stanford在内的顶级人工智能专家和学者们正在研究更复杂的任务：让机器像人类一样阅读文本，进而根据对该文本的理解来回答问题。这种阅读理解就像是让计算机来做我们高考英语的阅读理解题。

机器阅读理解（Reading comprehension）专知荟萃

入门学习

深度学习解决机器阅读理解任务的研究进展张俊林
- [https://zhuanlan.zhihu.com/p/22671467]
从短句到长文，计算机如何学习阅读理解微软亚洲研究院
- [http://www.msra.cn/zh-cn/news/features/machine-text-comprehension-20170508]
基于深度学习的阅读理解冯岩松
- [http://cips-upload.bj.bcebos.com/2017/ssatt2017/QA_2017_QAII.pdf]
SQuAD综述
- [https://www.jiqizhixin.com/articles/2017-05-21]
教机器学习阅读张俊
- [https://baijia.baidu.com/s?old_id=507397]
解读DeepMind的论文“教会机器阅读和理解”
- [http://www.jianshu.com/p/4da1dea4f541]
机器阅读理解中文章和问题的深度学习表示方法
- [http://blog.csdn.net/malefactor/article/details/52599733]

综述

Emergent Logical Structure in Vector Representations of Neural Readers
- [https://arxiv.org/pdf/1611.07954v1.pdf]
机器阅读理解任务综述林鸿宇韩先培
- [https://mp.weixin.qq.com/s?__biz=MzIxNzE2MTM4OA==&mid=2665643130&idx=1&sn=5f75f0d4978289caea6c4cb37b0b74c4]

进阶论文

Teaching Machines to Read and Comprehend
- [https://arxiv.org/abs/1506.03340]
Learning to Ask: Neural Question Generation for Reading Comprehension
- https://arxiv.org/pdf/1705.00106.pdf
Attention-over-Attention Neural Networks for Reading Comprehension
- https://arxiv.org/pdf/1607.04423.pdf
R-NET: MACHINE READING COMPREHENSION WITH SELF-MATCHING NETWORKS
- https://www.microsoft.com/en-us/research/wp-content/uploads/2017/05/r-net.pdf
Mnemonic Reader for Machine Comprehension
- https://arxiv.org/pdf/1705.02798.pdf
TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension
- https://arxiv.org/pdf/1705.03551.pdf
S-Net: From Answer Extraction to Answer Generation for Machine Reading Comprehension
- https://arxiv.org/pdf/1706.04815.pdf
RACE: Large-scale ReAding Comprehension Dataset From Examinations
- https://arxiv.org/pdf/1704.04683.pdf
Adversarial Examples for Evaluating Reading Comprehension Systems
- https://arxiv.org/pdf/1707.07328.pdf
Machine comprehension using match-lstm and answer pointer
- [https://arxiv.org/pdf/1608.07905]
Multi-perspective context matching for machine comprehension
- [https://arxiv.org/abs/1612.04211]
Reasonet: Learning to stop reading in machine comprehension
- [http://dl.acm.org/citation.cfm?id=3098177]
Learning recurrent span representations for extractive question answering
- [https://arxiv.org/abs/1611.01436]
End-to-end answer chunk extraction and ranking for reading comprehension
- [https://arxiv.org/abs/1610.09996]
Words or characters? fine-grained gating for reading comprehension
- [https://arxiv.org/abs/1611.01724]
Reading Wikipedia to Answer Open-Domain Questions
- [https://arxiv.org/abs/1704.00051]
An analysis of prerequisite skills for reading comprehension
- [http://www.aclweb.org/anthology/W/W16/W16-60.pdf#page=13]
A Comparative Study of Word Embeddings for Reading Comprehension
- https://arxiv.org/pdf/1703.00993.pdf