--- title: "Who cites Reasoning With Neural Tensor Networks for…" description: "254 papers of the Elamur Research library cite «Reasoning With Neural Tensor Networks for Knowledge Base Completion», found in their bibliographies; the…" canonical: "https://research.elamur.ai/free/en/papers/socher-2013-reasoning-neural-tensor-networks-knowledge/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/socher-2013-reasoning-neural-tensor-networks-knowledge/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Reasoning With Neural Tensor Networks for…](https://md.research.elamur.ai/free/en/papers/socher-2013-reasoning-neural-tensor-networks-knowledge/) / cited by # Who cites «Reasoning With Neural Tensor Networks for Knowledge Base Completion» 254 papers of our library cite it (of the 140,884 whose bibliographies we read) · 19 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/socher-2013-reasoning-neural-tensor-networks-knowledge/) 1. [**Distributed Representations of Sentences and Documents**Quoc V. Le, Tomas Mikolov*2014 · 5,747 citations*](https://md.research.elamur.ai/free/en/papers/le-2014-distributed-representations-sentences-documents/) 2. [**Knowledge Graphs**Aidan Hogan, Eva Blomqvist, Michael Cochez, et al.*2020 · 2,011 citations*](https://md.research.elamur.ai/free/en/papers/hogan-2020-knowledge-graphs/) 3. [**Modeling Relation Paths for Representation Learning of Knowledge Bases**Yankai Lin, Zhiyuan Liu, Huanbo Luan, et al.*2015 · 695 citations*](https://md.research.elamur.ai/free/en/papers/lin-2015-modeling-relation-paths-representation-learning/) 4. [**Effective LSTMs for Target-Dependent Sentiment Classification**Duyu Tang, Bing Qin, Xiaocheng Feng, et al.*2016 · 693 citations*](https://md.research.elamur.ai/free/en/papers/tang-2016-effective-lstms-target-dependent-sentiment/) 5. [**A Survey on Automated Fact-Checking**Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos*2022 · 646 citations*](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/) 6. [**Relation Extraction: Perspective from Convolutional Neural Networks**Thien Huu Nguyen, Ralph Grishman*2015 · 590 citations*](https://md.research.elamur.ai/free/en/papers/nguyen-2015-relation-extraction-perspective-convolutional-neural/) 7. [**Embedding Entities and Relations for Learning and Inference in Knowledge Bases**Bishan Yang, Wen-tau Yih, Xiaodong He, et al.*2014 · 458 citations*](https://md.research.elamur.ai/free/en/papers/yang-2014-embedding-entities-relations-learning-inference/) 8. [**Joint Learning of the Embedding of Words and Entities for Named Entity Disambiguation**Ikuya Yamada, Hiroyuki Shindo, Hideaki Takeda, et al.*2016 · 427 citations*](https://md.research.elamur.ai/free/en/papers/yamada-2016-joint-learning-embedding-words-entities/) 9. [**Commonsense Knowledge Base Completion**Xiang Li, Aynaz Taheri, Lifu Tu, et al.*2016 · 232 citations*](https://md.research.elamur.ai/free/en/papers/li-2016-commonsense-knowledge-base-completion/) 10. [**One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations**Yangfeng Ji, Jacob Eisenstein*2015 · 198 citations*](https://md.research.elamur.ai/free/en/papers/ji-2015-one-vector-is-not-enough/) 11. [**Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network**Jifan Chen, Qi Zhang, Pengfei Liu, et al.*2016 · 114 citations*](https://md.research.elamur.ai/free/en/papers/chen-2016-implicit-discourse-relation-detection-deep/) 12. [**Chinese Zero Pronoun Resolution with Deep Memory Network**Qingyu Yin, Yu Zhang, Weinan Zhang, et al.*2017 · 55 citations*](https://md.research.elamur.ai/free/en/papers/yin-2017-chinese-zero-pronoun-resolution-deep/) 13. [**Compositional Vector Space Models for Knowledge Base Completion**Arvind Neelakantan, Benjamin Roth, Andrew McCallum*2015 · 51 citations*](https://md.research.elamur.ai/free/en/papers/neelakantan-2015-compositional-vector-space-models-knowledge/) 14. [**Implicit Discourse Relation Recognition using Neural Tensor Network with Interactive Attention and Sparse Learning**Fengyu Guo, Ruifang He, Di Jin, et al.*2018 · 49 citations*](https://md.research.elamur.ai/free/en/papers/guo-2018-implicit-discourse-relation-recognition-neural/) 15. [**A Regularization Approach for Incorporating Event Knowledge and Coreference Relations into Neural Discourse Parsing**Zeyu Dai, Ruihong Huang*2019 · 46 citations*](https://md.research.elamur.ai/free/en/papers/dai-2019-regularization-approach-incorporating-event-knowledge/) 16. [**Topic Tensor Network for Implicit Discourse Relation Recognition in Chinese**Sheng Xu, Peifeng Li, Fang Kong, et al.*2019 · 31 citations*](https://md.research.elamur.ai/free/en/papers/xu-2019-topic-tensor-network-implicit-discourse/) 17. [**A Pragmatics-Centered Evaluation Framework for Natural Language Understanding**Damien Sileo, Philippe Muller, Tim Van de Cruys, et al.*2022 · 6 citations*](https://md.research.elamur.ai/free/en/papers/sileo-2022-pragmatics-centered-evaluation-framework-natural/) 18. [**Survey on Representation Learning Methods of Knowledge Graph for Link Prediction (面向链接预测的知识图谱表示学习方法综述)**Xueying Du (杜雪盈), Mingwei Liu (刘名威), Liwei Shen (沈立炜), et al.*2023*](https://md.research.elamur.ai/free/en/papers/du-2023-representation-learning-methods/) 19. [**Overview on Knowledge Graph Embedding Technology Research (知识图谱嵌入技术研究综述)**Tiancheng Zhang (张天成), Xue Tian (田雪), Xianghui Sun (孙相会), et al.*2021*](https://md.research.elamur.ai/free/en/papers/zhang-2021-overview-knowledge-graph/) 235 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/socher-2013-reasoning-neural-tensor-networks-knowledge/) — Reasoning With Neural Tensor Networks for Knowledge Base Completion