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Knowledge graphs (KGs) have helped neural models improve performance on various knowledge-intensive tasks, like question answering and item recommendation.
Attacking graph convolutional networks via rewiring
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Human-level control through deep reinforcement learning
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Embedding entities and relations for learning and inference in knowledge bases, 2015
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Conceptnet 5.5: An open multilingual graph of general knowledge
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Learning heterogeneous knowledge base embeddings for explainable recommendation
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Explainable knowledge graph-based recommendation via deep reinforcement learning
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Modeling relational data with graph convolutional networks
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Unifying knowledge graph learning and recommendation: Towards a better understanding of user preferences
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Knowledge-aware textual entailment with graph attention network
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Adversarial examples on graph data: Deep insights into attack and defense
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Interaction embeddings for prediction and explanation in knowledge graphs
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A survey of adversarial learning on graphs
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Scalable multi-hop relational reasoning for knowledge-aware question answering
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Graph-based reasoning over heterogeneous external knowledge for commonsense question answering
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Adversarial attacks on deep-learning models in natural language processing: A survey
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