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Question answering (QA) over knowledge bases (KBs) is challenging because of the diverse, essentially unbounded, types of reasoning patterns needed.
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Convolutional networks on graphs for learning molecular fingerprints
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Compositional vector space models for knowledge base completion
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Embedding entities and relations for learning and inference in knowledge bases
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Key-value memory networks for directly reading documents
Miller, A., Fisch, A., Dodge, J., Karimi, A.-H., Bordes, A., and Weston, J · 2016
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The value of semantic parse labeling for knowledge base question answering
Yih, W.-t., Richardson, M., Meek, C., Chang, M.-W., and Suh, J · 2016
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Neural message passing for quantum chemistry
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Kipf, T. N. and Welling, M · 2017
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Deeppath: A reinforcement learning method for knowledge graph reasoning
Xiong, W., Hoang, T., and Wang, W. Y · 2017
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Improved neural relation detection for knowledge base question answering
Yu, M., Yin, W., Hasan, K. S., Santos, C. d., Xiang, B., and Zhou, B · 2017
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Go for a walk and arrive at the answer: Reasoning over paths in knowledge bases using reinforcement learning
Das, R., Dhuliawala, S., Zaheer, M., Vilnis, L., Durugkar, I., Krishnamurthy, A., Smola, A., and McCallum, A · 2018
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How powerful are graph neural networks?
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Chen, T., Kornblith, S., Norouzi, M., and Hinton, G · 2020
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Scalable neural methods for reasoning with a symbolic knowledge base
Cohen, W. W., Sun, H., Hofer, R. A., and Siegler, M · 2020
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Entities as experts: Sparse memory access with entity supervision
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An empirical analysis of existing systems and datasets toward general simple question answering
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Gu, J., Wang, Y., Cho, K., and Li, V. O · 2018
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Strong baselines for simple question answering over knowledge graphs with and without neural networks
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Schlichtkrull, M., Kipf, T. N., Bloem, P., Van Den Berg, R., Titov, I., and Welling, M · 2018
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Open domain question answering using early fusion of knowledge bases and text
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Graph attention networks
Velickovic, P., Cucurull, G., Casanova, A., Romero, A., Liò, P., and Bengio, Y · 2018
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Generalization through memorization: Nearest neighbor language models
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Improving multi-hop question answering over knowledge graphs using knowledge base embeddings
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Infograph: Unsupervised and semi-supervised graph-level representation learning via mutual information maximization
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Inductive relation prediction by subgraph reasoning
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Facts as experts: Adaptable and interpretable neural memory over symbolic knowledge
Verga, P., Sun, H., Soares, L. B., and Cohen, W. W · 2020
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Graph contrastive learning with augmentations
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Deep graph contrastive representation learning
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Case-based reasoning for natural language queries over knowledge bases
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Improving multi-hop knowledge base question answering by learning intermediate supervision signals
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Nearest neighbor machine translation
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