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CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding
Data augmentation has been demonstrated as an effective strategy for imp...
10/16/2020 ∙ by Yanru Qu, et al. ∙
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Multi-document Summarization with Maximal Marginal Relevance-guided Reinforcement Learning
While neural sequence learning methods have made significant progress in...
09/30/2020 ∙ by Yuning Mao, et al. ∙
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A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation
Adversarial training has been shown effective at endowing the learned re...
09/29/2020 ∙ by Dinghan Shen, et al. ∙
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GIKT: A Graph-based Interaction Model for Knowledge Tracing
With the rapid development in online education, knowledge tracing (KT) h...
09/13/2020 ∙ by Yang Yang, et al. ∙
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An End-to-End Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation
This paper studies graph-based recommendation, where an interaction grap...
08/12/2019 ∙ by Yanru Qu, et al. ∙
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Dynamically Fused Graph Network for Multi-hop Reasoning
Text-based question answering (TBQA) has been studied extensively in rec...
05/16/2019 ∙ by Yunxuan Xiao, et al. ∙
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TGE-PS: Text-driven Graph Embedding with Pairs Sampling
In graphs with rich text information, constructing expressive graph repr...
09/12/2018 ∙ by Liheng Chen, et al. ∙
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Product-based Neural Networks for User Response Prediction over Multi-field Categorical Data
User response prediction is a crucial component for personalized informa...
07/01/2018 ∙ by Yanru Qu, et al. ∙
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Label-aware Double Transfer Learning for Cross-Specialty Medical Named Entity Recognition
We study the problem of named entity recognition (NER) from electronic m...
04/24/2018 ∙ by Zhenghui Wang, et al. ∙
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QA4IE: A Question Answering based Framework for Information Extraction
Information Extraction (IE) refers to automatically extracting structure...
04/10/2018 ∙ by Lin Qiu, et al. ∙
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Collaborative Filtering with Graph-based Implicit Feedback
Introducing consumed items as users' implicit feedback in matrix factori...
03/09/2018 ∙ by Minzhe Niu, et al. ∙
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Wasserstein Distance Guided Representation Learning for Domain Adaptation
Domain adaptation aims at generalizing a high-performance learner on a t...
07/05/2017 ∙ by Jian Shen, et al. ∙
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