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An Iterative Multi-Source Mutual Knowledge Transfer Framework for Machine Reading Comprehension

Xin Liu, Kai Liu, Xiang Li, Jinsong Su, Yubin Ge, Bin Wang, Jiebo Luo
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
In this paper, we propose a novel iterative multi-source mutual knowledge transfer framework for MRC.  ...  As an extension of the conventional knowledge transfer with one-to-one correspondence, our framework focuses on the many-to-many mutual transfer, which involves synchronous executions of multiple many-to-one  ...  Moreover, if we broaden our horizons to other types of knowledge-aware dialogue systems [Zhu et al., 2017; , some of them can also be transferred to commonsense knowledge-aware approaches.  ... 
doi:10.24963/ijcai.2020/521 dblp:conf/ijcai/Wu0ZZW20 fatcat:yexmetde3jgvlaae7uhu3v3lvy

Answer Generation through Unified Memories over Multiple Passages

Makoto Nakatsuji, Sohei Okui
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
Machine reading comprehension methods that gen- erate answers by referring to multiple passages for a question have gained much attention in AI and NLP communities.  ...  The current methods, however, do not investigate the relationships among multi- ple passages in the answer generation process, even though topics correlated among the passages may be answer candidates.  ...  We also thank the reviewers for their insightful comments. Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  ... 
doi:10.24963/ijcai.2020/525 dblp:conf/ijcai/LiuLLSGWL20 fatcat:zjzv6wadjbenjcrra6mrhxbmtm

Heterogeneous Information Knowledge Construction Based on Ontology

Jianhou Gan, Gang Xie, Yongzheng Yan, Wanquan Liu
2016 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
Moreover, a knowledge base construction framework for multi-source heterogeneous information source with combination of Ontology knowledge model is put forward, and an algorithm of knowledge base construction  ...  After investigating knowledge forming process based on multi-source heterogeneous information resources, we present a new approach in which different information resources are put into a mutual RDF(S)  ...  Knowledge Basis Construction Framework for Multi-source Heterogeneous Information Resources 3.1.  ... 
doi:10.12928/telkomnika.v14i4.4787 fatcat:dr33t5xxnneoflhsv6rs5xgvsu

A Study of the Tasks and Models in Machine Reading Comprehension [article]

Chao Wang
2020 arXiv   pre-print
To provide a survey on the existing tasks and models in Machine Reading Comprehension (MRC), this report reviews: 1) the dataset collection and performance evaluation of some representative simple-reasoning  ...  and complex-reasoning MRC tasks; 2) the architecture designs, attention mechanisms, and performance-boosting approaches for developing neural-network-based MRC models; 3) some recently proposed transfer  ...  Introduction Machine Reading Comprehension (MRC) requires a machine to read a context and answer a set of relevant questions based on its comprehension of the context.  ... 
arXiv:2001.08635v1 fatcat:yuc3fx4jjvhkxnbv4o6kerunve

Multi-Task Optimization and Multi-Task Evolutionary Computation in the Past Five Years: A Brief Review

Qingzheng Xu, Na Wang, Lei Wang, Wei Li, Qian Sun
2021 Mathematics  
Inspired by this concept, the paradigm of multi-task evolutionary computation (MTEC) has recently emerged as an effective means of facilitating implicit or explicit knowledge transfer across optimization  ...  tasks, thereby potentially accelerating convergence and improving the quality of solutions for multi-task optimization problems.  ...  All authors have read and agreed to the published version of the manuscript. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/math9080864 fatcat:nnkdm4zkwvaxveh5cvblhbk5ve

Knowledge Distillation: A Survey [article]

Jianping Gou, Baosheng Yu, Stephen John Maybank, Dacheng Tao
2021 arXiv   pre-print
This paper provides a comprehensive survey of knowledge distillation from the perspectives of knowledge categories, training schemes, teacher-student architecture, distillation algorithms, performance  ...  In recent years, deep neural networks have been successful in both industry and academia, especially for computer vision tasks.  ...  For question answering, to improve the efficiency and robustness of machine reading comprehension, Hu et al. (2018) proposed an attention-guided answer distillation method, which fuses generic distillation  ... 
arXiv:2006.05525v6 fatcat:aedzaeln5zf3jgjsgsn5kvjrri

Benchmarking Machine Reading Comprehension: A Psychological Perspective [article]

Saku Sugawara, Pontus Stenetorp, Akiko Aizawa
2021 arXiv   pre-print
Machine reading comprehension (MRC) has received considerable attention as a benchmark for natural language understanding.  ...  ., reading comprehension by a model cannot be explained in human terms.  ...  Acknowledgments The authors would like to thank Xanh Ho for helping create the dataset list and the anonymous reviewers for their insightful comments.  ... 
arXiv:2004.01912v2 fatcat:lyypngwm4vbk7igfcjfmhkn5ja

Model Compression with Multi-Task Knowledge Distillation for Web-scale Question Answering System [article]

Ze Yang, Linjun Shou, Ming Gong, Wutao Lin, Daxin Jiang
2019 arXiv   pre-print
To tackle this challenge, we propose a Multi-task Knowledge Distillation Model (MKDM for short) for web-scale Question Answering system, by distilling knowledge from multiple teacher models to a light-weight  ...  In this way, more generalized knowledge can be transferred.  ...  On the other side, we will extend our methods to more tasks, such like sentence classification, machine reading comprehension, etc.  ... 
arXiv:1904.09636v1 fatcat:mjmd6igfavddjlgmj6szvsrb5a

First-principle study on honeycomb fluorated-InTe monolayer with large Rashba spin splitting and direct bandgap

Kaixuan Li, Xiujuan Xian, Jiafu Wang, Niannian Yu
2019 Applied Surface Science  
Machine reading comprehension (MRC), which requires a machine to answer questions based on a given context, has attracted increasing attention with the incorporation of various deep-learning techniques  ...  Although research on MRC based on deep learning is flourishing, there remains a lack of a comprehensive survey summarizing existing approaches and recent trends, which motivated the work presented in this  ...  Conclusion This article presents a comprehensive survey on the progresses of neural machine reading comprehension.  ... 
doi:10.1016/j.apsusc.2018.11.214 fatcat:dg2eusl7ufhttcsqlllyiisxb4

Neural Machine Reading Comprehension: Methods and Trends

Shanshan Liu, Xin Zhang, Sheng Zhang, Hui Wang, Weiming Zhang
2019 Applied Sciences  
Machine reading comprehension (MRC), which requires a machine to answer questions based on a given context, has attracted increasing attention with the incorporation of various deep-learning techniques  ...  Although research on MRC based on deep learning is flourishing, there remains a lack of a comprehensive survey summarizing existing approaches and recent trends, which motivated the work presented in this  ...  [45] extend MRC to machine reading at scale, more widely called multi-passage machine reading comprehension, which does not give one relevant passage for each question, unlike the traditional task.  ... 
doi:10.3390/app9183698 fatcat:bpwwfikrpvh4dhphyl3ezpnn5e

GrandBase: generating actionable knowledge from Big Data

Xiu Susie Fang, Quan Z. Sheng, Xianzhi Wang, Anne H.H. Ngu, Yihong Zhang
2017 PSU Research Review  
Purpose -This paper aims to propose a system for generating actionable knowledge from Big Data and use this system to construct a comprehensive knowledge base (KB), called GrandBase.  ...  In addition, a graph-based approach to conduct better truth discovery for multi-valued predicates is also proposed.  ...  Such knowledge holds the potential to efficiently and effectively change human lives by enabling technologies such as disambiguation, deep reasoning, machine reading, semantic search in terms of entities  ... 
doi:10.1108/prr-01-2017-0005 fatcat:qr2r4f73ffcfjah7oocgsscqp4

Exploring the Development of Research, Technology and Business of Machine Tool Domain in New-Generation Information Technology Environment Based on Machine Learning

Jihong Chen, Kai Zhang, Yuan Zhou, Yufei Liu, Lingfeng Li, Zheng Chen, Li Yin
2019 Sustainability  
To solve this challenge, we propose an integrating framework combining topic models, bibliometric, trend analysis and patent analysis to mine multi-source literature within the machine tool domain, including  ...  The integration of above various analytical methods and multi-dimensional mining of literature enabled analyzing the development of the machine tool domain systematically from multi-perspectives that include  ...  In this paper, we proposed an integrating framework to solve the above challenge by analyzing multi-source literature.  ... 
doi:10.3390/su11123316 fatcat:i2sb6xsybbecxdau2qbima2bxq

Knowledge Efficient Deep Learning for Natural Language Processing [article]

Hai Wang
2020 arXiv   pre-print
Fourth, we present an episodic memory network for language modelling, in which we encode the large external knowledge for the pre-trained GPT.  ...  First, we propose a knowledge rich deep learning model (KRDL) as a unifying learning framework for incorporating prior knowledge into deep models.  ...  Code-Mixed Machine Reading Comprehension: We consider the mixed-language machine reading comprehension task.  ... 
arXiv:2008.12878v1 fatcat:vhcxrhydyfcsnh3iu5t3g5goky

A Weight Based Labeled Classifier Using Machine Learning Technique for Classification of Medical Data

Mohammed Zaheer Ahmed, Chitraivel Mahesh
2021 Revue d'intelligence artificielle : Revue des Sciences et Technologies de l'Information  
The usage of machine intelligence techniques enhances efficiency and reduces the error rate which strengthens health treatment for patients.  ...  It covers scientific knowledge and genetic data, as well as the principle of biomedical computation. Data observations across the world have been spread in the past several years.  ...  PROPOSED MODEL There are many real-world implementations where the goal brands are not mutually identical and need a multi-label distinction.  ... 
doi:10.18280/ria.350104 fatcat:ki6lxkbn6jgwbac4moiqtgiu5e

Recent Advances in Deep Learning Based Dialogue Systems: A Systematic Survey [article]

Jinjie Ni, Tom Young, Vlad Pandelea, Fuzhao Xue, Erik Cambria
2022 arXiv   pre-print
To the best of our knowledge, this survey is the most comprehensive and up-to-date one at present for deep learning based dialogue systems, extensively covering the popular techniques.  ...  Furthermore, we comprehensively review the evaluation methods and datasets for dialogue systems to pave the way for future research.  ...  Tay et al. (2019) used a pointer-generator framework to perform machine reading comprehension over a long span, where the copy mechanism reduced the demand of including target answers in context.  ... 
arXiv:2105.04387v5 fatcat:yd3gqg45rjgzxbiwfdlcvf3pye
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