--- title: "Who cites Embedding Entities and Relations for Learning…" description: "458 papers of the Elamur Research library cite «Embedding Entities and Relations for Learning and Inference in Knowledge Bases», found in their…" canonical: "https://research.elamur.ai/free/en/papers/yang-2014-embedding-entities-relations-learning-inference/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yang-2014-embedding-entities-relations-learning-inference/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Embedding Entities and Relations for Learning and…](https://md.research.elamur.ai/free/en/papers/yang-2014-embedding-entities-relations-learning-inference/) / cited by # Who cites «Embedding Entities and Relations for Learning and Inference in Knowledge Bases» 458 papers of our library cite it (of the 140,884 whose bibliographies we read) · 16 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/yang-2014-embedding-entities-relations-learning-inference/) 1. [**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/) 2. [**Unifying Large Language Models and Knowledge Graphs: A Roadmap**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,545 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/) 3. [**Representing Text for Joint Embedding of Text and Knowledge Bases**Kristina Toutanova, Danqi Chen, Patrick Pantel, et al.*2015 · 904 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2015-representing-text-joint-embedding-text/) 4. [**TuckER: Tensor Factorization for Knowledge Graph Completion**Ivana Balažević, Carl Allen, Timothy M. Hospedales*2019 · 792 citations*](https://md.research.elamur.ai/free/en/papers/balazevic-2019-tucker-tensor-factorization-knowledge-graph/) 5. [**Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings**Apoorv Saxena, Aditay Tripathi, Partha Talukdar*2020 · 670 citations*](https://md.research.elamur.ai/free/en/papers/saxena-2020-improving-multi-hop-question-answering/) 6. [**How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence**Haoxi Zhong, Chaojun Xiao, Cunchao Tu, et al.*2020 · 518 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2020-how-does-nlp-benefit-legal/) 7. [**LinkBERT: Pretraining Language Models with Document Links**Michihiro Yasunaga, Jure Leskovec, Percy Liang*2022 · 452 citations*](https://md.research.elamur.ai/free/en/papers/yasunaga-2022-linkbert-pretraining-language-models-document/) 8. [**Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge**Todor Mihaylov, Anette Frank*2018 · 260 citations*](https://md.research.elamur.ai/free/en/papers/mihaylov-2018-knowledgeable-reader-enhancing-cloze-style/) 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. [**Observed versus latent features for knowledge base and text inference**Kristina Toutanova, Danqi Chen*2015 · 210 citations*](https://md.research.elamur.ai/free/en/papers/toutanova-2015-observed-versus-latent-features-knowledge/) 11. [**Dipping PLMs Sauce: Bridging Structure and Text for Effective Knowledge Graph Completion via Conditional Soft Prompting**Chen Chen, Yufei Wang, Aixin Sun, et al.*2023 · 75 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-dipping-plms-sauce-bridging-structure/) 12. [**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/) 13. [**Exploiting Sentiment and Common Sense for Zero-shot Stance Detection**Yun Luo, Zihan Liu, Yuefeng Shi, et al.*2022 · 30 citations*](https://md.research.elamur.ai/free/en/papers/luo-2022-exploiting-sentiment-common-sense-zero/) 14. [**Research Progress and Trend of Temporal Knowledge Graph Representation and Reasoning (时序知识图谱表示与推理的研究进展与趋势)**Yuhan Wang (王俞涵), Ziyang Chen (陈子阳), Xiang Zhao (赵翔), et al.*2024*](https://md.research.elamur.ai/free/en/papers/wang-2024-trend-temporal-knowledge/) 15. [**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/) 16. [**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/) 442 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/yang-2014-embedding-entities-relations-learning-inference/) — Embedding Entities and Relations for Learning and Inference in Knowledge Bases