---
title: "Who cites Translating Embeddings for — 986 citing papers"
description: "986 papers of the Elamur Research library cite «Translating Embeddings for Modeling Multi-relational Data», found in their bibliographies; the…"
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---
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# Who cites «Translating Embeddings for Modeling Multi-relational Data»

986 papers of our library cite it (of the 149,439 whose bibliographies we read) · 66 with a page here, the most cited first · [← back to «Translating Embeddings for Modeling Multi-relational Data»](https://md.research.elamur.ai/free/en/papers/bordes-2013-translating-embeddings-modeling-multi-relational/)

1. **[Language Models as Knowledge Bases?](https://md.research.elamur.ai/free/en/papers/petroni-2019-language-models-as-knowledge-bases/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, et al.*2019 · 3,028 citations*
2. [**Embedding Entities and Relations for Learning and Inference in Knowledge Bases arXiv:1412.6575**Bishan Yang, Wen-tau Yih, Xiaodong He, et al.*2014 · 2,370 citations*](https://md.research.elamur.ai/free/en/papers/yang-2014-embedding-entities-relations-learning-inference/)
3. [**Relational inductive biases, deep learning, and graph networks arXiv:1806.01261**Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, et al.*2018 · 2,335 citations*](https://md.research.elamur.ai/free/en/papers/battaglia-2018-relational-inductive-biases-deep-learning/)
4. **[Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/hogan-2020-knowledge-graphs/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Aidan Hogan, Eva Blomqvist, Michael Cochez, et al.*2020 · 2,014 citations*
5. **[Unifying Large Language Models and Knowledge Graphs: A Roadmap](https://md.research.elamur.ai/free/en/papers/pan-2023-unifying-large-language-models-knowledge/) [IEEE Transactions on Knowledge and Data Engineering](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-knowledge-and-data-engineering/)**Shirui Pan, Linhao Luo, Yufei Wang, et al.*2023 · 1,551 citations*
6. [**Complex Embeddings for Simple Link Prediction arXiv:1606.06357**Théo Trouillon, Johannes Welbl, Sebastian Riedel, et al.*2016 · 1,489 citations*](https://md.research.elamur.ai/free/en/papers/trouillon-2016-complex-embeddings-simple-link-prediction/)
7. **[Observed versus latent features for knowledge base and text inference](https://md.research.elamur.ai/free/en/papers/toutanova-2015-observed-versus-latent-features-knowledge/) [Workshop on Continuous Vector Space Models and their Compositionality](https://md.research.elamur.ai/free/en/venues/workshop-on-continuous-vector-space-models-and-their-compositionality/)**Kristina Toutanova, Danqi Chen*2015 · 1,243 citations*
8. [**RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space arXiv:1902.10197**Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, et al.*2019 · 1,073 citations*](https://md.research.elamur.ai/free/en/papers/sun-2019-rotate-knowledge-graph-embedding-relational/)
9. **[K-BERT: Enabling Language Representation with Knowledge Graph](https://md.research.elamur.ai/free/en/papers/liu-2019-k-bert-enabling-language-representation/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Weijie Liu, Peng Zhou, Zhe Zhao, et al.*2019 · 1,019 citations*
10. **[Matching the Blanks: Distributional Similarity for Relation Learning](https://md.research.elamur.ai/free/en/papers/soares-2019-matching-blanks-distributional-similarity-relation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Livio Baldini Soares, Nicholas FitzGerald, Jeffrey Ling, et al.*2019 · 999 citations*
11. **[A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network](https://md.research.elamur.ai/free/en/papers/nguyen-2018-novel-embedding-model-knowledge-base/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, et al.*2018 · 946 citations*
12. **[Representing Text for Joint Embedding of Text and Knowledge Bases](https://md.research.elamur.ai/free/en/papers/toutanova-2015-representing-text-joint-embedding-text/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kristina Toutanova, Danqi Chen, Patrick Pantel, et al.*2015 · 907 citations*
13. [**TuckER: Tensor Factorization for Knowledge Graph Completion arXiv:1901.09590**Ivana Balažević, Carl Allen, Timothy M. Hospedales*2019 · 799 citations*](https://md.research.elamur.ai/free/en/papers/balazevic-2019-tucker-tensor-factorization-knowledge-graph/)
14. **[Modeling Relation Paths for Representation Learning of Knowledge Bases](https://md.research.elamur.ai/free/en/papers/lin-2015-modeling-relation-paths-representation-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yankai Lin, Zhiyuan Liu, Huanbo Luan, et al.*2015 · 702 citations*
15. **[Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks](https://md.research.elamur.ai/free/en/papers/wang-2018-cross-lingual-knowledge-graph-alignment/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhichun Wang, Qingsong Lv, Xiaohan Lan, et al.*2018 · 685 citations*
16. **[Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings](https://md.research.elamur.ai/free/en/papers/saxena-2020-improving-multi-hop-question-answering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Apoorv Saxena, Aditay Tripathi, Partha Talukdar*2020 · 671 citations*
17. [**K-Adapter: Infusing Knowledge into Pre-Trained Models with Adapters arXiv:2002.01808**Ruize Wang, Duyu Tang, Nan Duan, et al.*2020 · 666 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-k-adapter-infusing-knowledge-pre/)
18. **[A Survey on Automated Fact-Checking](https://md.research.elamur.ai/free/en/papers/guo-2022-survey-automated-fact-checking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Zhijiang Guo, Michael Schlichtkrull, Andreas Vlachos*2022 · 647 citations*
19. **[MIND: A Large-scale Dataset for News Recommendation](https://md.research.elamur.ai/free/en/papers/wu-2020-mind-large-scale-dataset-news/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fangzhao Wu, Ying Qiao, Jiun-Hung Chen, et al.*2020 · 564 citations*
20. **[How Does NLP Benefit Legal System: A Summary of Legal Artificial Intelligence](https://md.research.elamur.ai/free/en/papers/zhong-2020-how-does-nlp-benefit-legal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoxi Zhong, Chaojun Xiao, Cunchao Tu, et al.*2020 · 518 citations*
21. **[Knowledge Graph and Text Jointly Embedding](https://md.research.elamur.ai/free/en/papers/wang-2014-knowledge-graph-text-jointly-embedding/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhen Wang, Jianwen Zhang, Jianlin Feng, et al.*2014 · 461 citations*
22. **[LinkBERT: Pretraining Language Models with Document Links](https://md.research.elamur.ai/free/en/papers/yasunaga-2022-linkbert-pretraining-language-models-document/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michihiro Yasunaga, Jure Leskovec, Percy Liang*2022 · 458 citations*
23. **[OpenDialKG: Explainable Conversational Reasoning with Attention-based Walks over Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/moon-2019-opendialkg-explainable-conversational-reasoning-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seungwhan Moon, Pararth Shah, Anuj Kumar, et al.*2019 · 449 citations*
24. **[A general framework for information extraction using dynamic span graphs](https://md.research.elamur.ai/free/en/papers/luan-2019-general-framework-information-extraction-dynamic/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Yi Luan, Dave Wadden, Luheng He, et al.*2019 · 431 citations*
25. **[Low-Dimensional Hyperbolic Knowledge Graph Embeddings](https://md.research.elamur.ai/free/en/papers/chami-2020-low-dimensional-hyperbolic-knowledge-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ines Chami, Adva Wolf, Da-Cheng Juan, et al.*2020 · 429 citations*
26. [**FiLM: Visual Reasoning with a General Conditioning Layer arXiv:1709.07871**Ethan Perez, Florian Strub, Harm de Vries, et al.*2017 · 400 citations*](https://md.research.elamur.ai/free/en/papers/perez-2017-film-visual-reasoning-general-conditioning/)
27. **[SensEmbed: Learning Sense Embeddings for Word and Relational Similarity](https://md.research.elamur.ai/free/en/papers/iacobacci-2015-sensembed-learning-sense-embeddings-word/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ignacio Iacobacci, Mohammad Taher Pilehvar, Roberto Navigli*2015 · 349 citations*
28. [**Poincaré Embeddings for Learning Hierarchical Representations arXiv:1705.08039**Maximilian Nickel, Douwe Kiela*2017 · 336 citations*](https://md.research.elamur.ai/free/en/papers/nickel-2017-poincare-embeddings-learning-hierarchical-representations/)
29. **[Neural Natural Language Inference Models Enhanced with External Knowledge](https://md.research.elamur.ai/free/en/papers/chen-2018-neural-natural-language-inference-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, et al.*2018 · 315 citations*
30. **[Entity Linking via Joint Encoding of Types, Descriptions, and Context](https://md.research.elamur.ai/free/en/papers/gupta-2017-entity-linking-joint-encoding-types/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nitish Gupta, Sameer Singh, Dan Roth*2017 · 299 citations*
31. **[Compositional Vector Space Models for Knowledge Base Completion](https://md.research.elamur.ai/free/en/papers/neelakantan-2015-compositional-vector-space-models-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Arvind Neelakantan, Benjamin Roth, Andrew McCallum*2015 · 281 citations*
32. **[Knowledgeable Reader: Enhancing Cloze-Style Reading Comprehension with External Commonsense Knowledge](https://md.research.elamur.ai/free/en/papers/mihaylov-2018-knowledgeable-reader-enhancing-cloze-style/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Todor Mihaylov, Anette Frank*2018 · 263 citations*
33. **[CoLAKE: Contextualized Language and Knowledge Embedding](https://md.research.elamur.ai/free/en/papers/sun-2020-colake-contextualized-language-knowledge-embedding/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tianxiang Sun, Yunfan Shao, Xipeng Qiu, et al.*2020 · 239 citations*
34. **[Commonsense Knowledge Base Completion](https://md.research.elamur.ai/free/en/papers/li-2016-commonsense-knowledge-base-completion/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiang Li, Aynaz Taheri, Lifu Tu, et al.*2016 · 234 citations*
35. **[Entities as Experts: Sparse Memory Access with Entity Supervision](https://md.research.elamur.ai/free/en/papers/fevry-2020-entities-as-experts-sparse-memory/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thibault Févry, Livio Baldini Soares, Nicholas FitzGerald, et al.*2020 · 208 citations*
36. **[Grounded Conversation Generation as Guided Traverses in Commonsense Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/zhang-2020-grounded-conversation-generation-as-guided/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Houyu Zhang, Zhenghao Liu, Chenyan Xiong, et al.*2020 · 183 citations*
37. **[Molweni: A Challenge Multiparty Dialogues-based Machine Reading Comprehension Dataset with Discourse Structure](https://md.research.elamur.ai/free/en/papers/li-2020-molweni-challenge-multiparty-dialogues-based/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jiaqi Li, Ming Liu, Min-Yen Kan, et al.*2020 · 141 citations*
38. **[Enhancing Zero-shot and Few-shot Stance Detection with Commonsense Knowledge Graph](https://md.research.elamur.ai/free/en/papers/liu-2021-enhancing-zero-shot-few-shot/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Liu, Zheng Lin, Yutong Tan, et al.*2021 · 134 citations*
39. **[STransE: a novel embedding model of entities and relationships in knowledge bases](https://md.research.elamur.ai/free/en/papers/nguyen-2016-stranse-novel-embedding-model-entities/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Dat Quoc Nguyen, Kairit Sirts, Lizhen Qu, et al.*2016 · 130 citations*
40. **[Overcoming Language Variation in Sentiment Analysis with Social Attention](https://md.research.elamur.ai/free/en/papers/yang-2017-overcoming-language-variation-sentiment-analysis/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Yi Yang, Jacob Eisenstein*2017 · 119 citations*
41. **[Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/nathani-2019-learning-attention-based-embeddings-relation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deepak Nathani, Jatin Chauhan, Charu Sharma, et al.*2019 · 108 citations*
42. **[Does William Shakespeare REALLY Write Hamlet? Knowledge Representation Learning with Confidence](https://md.research.elamur.ai/free/en/papers/xie-2017-william-shakespeare-really-write-hamlet/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Ruobing Xie, Zhiyuan Liu, Fen Lin, et al.*2017 · 93 citations*
43. **[Dipping PLMs Sauce: Bridging Structure and Text for Effective Knowledge Graph Completion via Conditional Soft Prompting](https://md.research.elamur.ai/free/en/papers/chen-2023-dipping-plms-sauce-bridging-structure/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chen Chen, Yufei Wang, Aixin Sun, et al.*2023 · 75 citations*
44. **[Multi-Relational Script Learning for Discourse Relations](https://md.research.elamur.ai/free/en/papers/lee-2019-multi-relational-script-learning-discourse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**I-Ta Lee, Dan Goldwasser*2019 · 66 citations*
45. [**Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners arXiv:2305.14825**Xiaojuan Tang, Zilong Zheng, Jiaqi Li, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/tang-2023-large-language-models-context-semantic/)
46. **[A Regularization Approach for Incorporating Event Knowledge and Coreference Relations into Neural Discourse Parsing](https://md.research.elamur.ai/free/en/papers/dai-2019-regularization-approach-incorporating-event-knowledge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zeyu Dai, Ruihong Huang*2019 · 46 citations*
47. **[A Survey of Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/xiang-2022-survey-implicit-discourse-relation-recognition/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Wei Xiang, Bang Wang*2022 · 43 citations*
48. **[TransS-Driven Joint Learning Architecture for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/he-2020-transs-driven-joint-learning-architecture/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruifang He, Jian Wang, Fengyu Guo, et al.*2020 · 41 citations*
49. **[Contextualization Distillation from Large Language Model for Knowledge Graph Completion](https://md.research.elamur.ai/free/en/papers/li-2024-contextualization-distillation-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Dawei Li, Zhen Tan, Tianlong Chen, et al.*2024 · 30 citations*
50. [**SherLIiC: A Typed Event-Focused Lexical Inference Benchmark for Evaluating Natural Language Inference**Martin Schmitt, Hinrich Schütze*2019 · 28 citations*](https://md.research.elamur.ai/free/en/papers/schmitt-2019-sherliic-typed-event-focused-lexical/)
51. **[Weakly-Supervised Modeling of Contextualized Event Embedding for Discourse Relations](https://md.research.elamur.ai/free/en/papers/lee-2020-weakly-supervised-modeling-contextualized-event/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**I-Ta Lee, Maria Leonor Pacheco, Dan Goldwasser*2020 · 23 citations*
52. [**Understanding Finetuning for Factual Knowledge Extraction from Language Models arXiv:2301.11293**Mehran Kazemi, Sid Mittal, Deepak Ramachandran*2023 · 11 citations*](https://md.research.elamur.ai/free/en/papers/kazemi-2023-understanding-finetuning-factual-knowledge-extraction/)
53. [**Survey on English Entity Linking on Wikidata arXiv:2112.01989**Cedric Möller, Jens Lehmann, Ricardo Usbeck*2021 · 10 citations*](https://md.research.elamur.ai/free/en/papers/moller-2021-survey-english-entity-linking-wikidata/)
54. [**From Statistical Relational to Neurosymbolic Artificial Intelligence: a Survey arXiv:2108.11451**Giuseppe Marra, Sebastijan Dumančić, Robin Manhaeve, et al.*2021 · 3 citations*](https://md.research.elamur.ai/free/en/papers/marra-2021-statistical-relational-neurosymbolic-artificial/)
55. **[Joint Knowledge Base Completion and Question Answering by Combining Large Language Models and Small Language Models](https://md.research.elamur.ai/free/en/papers/liu-2026-joint-knowledge-base-completion-question/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yinan Liu, Dongying Lin, Sigang Luo, et al.*2026 · 2 citations*
56. **[Combining Semantic Embeddings and Knowledge Graphs for Identifying Decision Patterns in Brazilian Judicial Decisions](https://md.research.elamur.ai/free/en/papers/silva-2026-combining-semantic-embeddings-knowledge-graphs/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Gustavo Soares Silva, Omar Andres Carmona Cortes, Fábio Manoel França Lobato, et al.*2026*
57. **[EA-Agent: A Structured Multi-Step Reasoning Agent for Entity Alignment](https://md.research.elamur.ai/free/en/papers/nan-2026-ea-agent-structured-multi-step/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixuan Nan, Xixun Lin, Yanmin Shang, et al.*2026*
58. **[Linguistic Initialization for Inductive Reasoning in Heterogeneous Knowledge Graphs](https://md.research.elamur.ai/free/en/papers/pasquini-2026-linguistic-initialization-inductive-reasoning-heterogeneous/) [Knowledge Graphs and Large Language Models Workshop (KG-LLM) @ LREC26](https://md.research.elamur.ai/free/en/venues/kallm/)**Daniele Pasquini, Danilo Croce, Roberto Basili*2026*
59. **[MAGIC: Deep Geometric Evolution with Structural Consensus for Temporal Knowledge Graph Reasoning](https://md.research.elamur.ai/free/en/papers/liu-2026-magic-deep-geometric-evolution-structural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chengao Liu, Yuan Li, Yingze Wang, et al.*2026*
60. **[MuSe: Multi-Stage Graph Reasoning via Vision-Language Models](https://md.research.elamur.ai/free/en/papers/wang-2026-muse-multi-stage-graph-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guanyu Wang, Xu Chu, Zhijie Tan, et al.*2026*
61. **[Not All Modalities at Once: Dynamic Dropout and Bidirectional Fusion for Robust Multi-modal Knowledge Graph Completion](https://md.research.elamur.ai/free/en/papers/peng-2026-not-all-modalities-once-dynamic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jiashun Peng, Fu Zhang, Hongzhi Chen, et al.*2026*
62. **[Risk-Controlled Event-Driven Cascading Updates for Knowledge Graph Consistency Restoration](https://md.research.elamur.ai/free/en/papers/ni-2026-risk-controlled-event-driven-cascading/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Bo Ni, Qinwen Ge, Haowei Fu, et al.*2026*
63. **[Simulating Sense Extension](https://md.research.elamur.ai/free/en/papers/maudslay-2026-simulating-sense-extension/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Rowan Hall Maudslay, Simone Teufel*2026*
64. **[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)](https://md.research.elamur.ai/free/en/papers/wang-2024-trend-temporal-knowledge/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Yuhan Wang (王俞涵), Ziyang Chen (陈子阳), Xiang Zhao (赵翔), et al.*2024*
65. **[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)](https://md.research.elamur.ai/free/en/papers/du-2023-representation-learning-methods/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Xueying Du (杜雪盈), Mingwei Liu (刘名威), Liwei Shen (沈立炜), et al.*2023*
66. **[Overview on Knowledge Graph Embedding Technology Research (知识图谱嵌入技术研究综述)](https://md.research.elamur.ai/free/en/papers/zhang-2021-overview-knowledge-graph/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Tiancheng Zhang (张天成), Xue Tian (田雪), Xianghui Sun (孙相会), et al.*2021*

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