---
title: "Who cites Markus Krötzsch — 675 papers of our library"
description: "675 papers of the Elamur Research library cite the works of Markus Krötzsch, found in their bibliographies; the most cited first."
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---
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# Who cites Markus Krötzsch

678 citations of their works from 675 papers of our library (of the 149,439 whose bibliographies we read) · 66 with a page here, the most cited first · [← Markus Krötzsch](https://md.research.elamur.ai/free/en/authors/markus-krotzsch/)

1. **[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*
2. **[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*
3. **[StereoSet: Measuring stereotypical bias in pretrained language models](https://md.research.elamur.ai/free/en/papers/nadeem-2021-stereoset-measuring-stereotypical-bias-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Moin Nadeem, Anna Bethke, Siva Reddy*2021 · 1,141 citations*
4. **[oLMpics — On what Language Model Pre-training Captures](https://md.research.elamur.ai/free/en/papers/talmor-2019-olmpics-language-model-pre-training/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Alon Talmor, Yanai Elazar, Yoav Goldberg, et al.*2019 · 440 citations*
5. **[Latent Hatred: A Benchmark for Understanding Implicit Hate Speech](https://md.research.elamur.ai/free/en/papers/elsherief-2021-latent-hatred-benchmark-understanding-implicit/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mai ElSherief, Caleb Ziems, David Muchlinski, et al.*2021 · 367 citations*
6. **[Time-Aware Language Models as Temporal Knowledge Bases](https://md.research.elamur.ai/free/en/papers/dhingra-2022-time-aware-language-models-as/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos, et al.*2022 · 349 citations*
7. **[Entity-Based Knowledge Conflicts in Question Answering](https://md.research.elamur.ai/free/en/papers/longpre-2021-entity-based-knowledge-conflicts-question/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shayne Longpre, Kartik Perisetla, Anthony Chen, et al.*2021 · 298 citations*
8. **[XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation](https://md.research.elamur.ai/free/en/papers/ruder-2021-xtreme-r-more-challenging-nuanced/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Sebastian Ruder, Noah Constant, Jan Botha, et al.*2021 · 281 citations*
9. **[Graph Retrieval-Augmented Generation: A Survey](https://md.research.elamur.ai/free/en/papers/peng-2024-graph-retrieval-augmented-generation-survey/) [ACM Transactions on Information Systems](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-information-systems/)**Boci Peng, Yun Zhu, Yongchao Liu, et al.*2024 · 276 citations*
10. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 273 citations*
11. **[BPEmb: Tokenization-free Pre-trained Subword Embeddings in 275 Languages](https://md.research.elamur.ai/free/en/papers/heinzerling-2018-bpemb-tokenization-free-pre-trained/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Benjamin Heinzerling, Michael Strube*2018 · 257 citations*
12. **[Learning from Context or Names? An Empirical Study on Neural Relation Extraction](https://md.research.elamur.ai/free/en/papers/peng-2020-learning-context-or-names-empirical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hao Peng, Tianyu Gao, Xu Han, et al.*2020 · 255 citations*
13. **[KGPT: Knowledge-Grounded Pre-Training for Data-to-Text Generation](https://md.research.elamur.ai/free/en/papers/chen-2020-kgpt-knowledge-grounded-pre-training/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Wenhu Chen, Yu Su, Xifeng Yan, et al.*2020 · 174 citations*
14. [**Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity arXiv:2310.07521**Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, et al.*2023 · 171 citations*](https://md.research.elamur.ai/free/en/papers/wang-2023-survey-factuality-large-language-models/)
15. **[Personalized Machine Translation: Preserving Original Author Traits](https://md.research.elamur.ai/free/en/papers/rabinovich-2017-personalized-machine-translation-preserving-original/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ella Rabinovich, Raj Nath Patel, Shachar Mirkin, et al.*2017 · 170 citations*
16. **[Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/tan-2022-document-level-relation-extraction-adaptive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qingyu Tan, Ruidan He, Lidong Bing, et al.*2022 · 169 citations*
17. **[Simple Entity-Centric Questions Challenge Dense Retrievers](https://md.research.elamur.ai/free/en/papers/sciavolino-2021-simple-entity-centric-questions-challenge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Christopher Sciavolino, Zexuan Zhong, Jinhyuk Lee, et al.*2021 · 169 citations*
18. **[Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction](https://md.research.elamur.ai/free/en/papers/zhang-2024-extract-define-canonicalize-llm-based/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bowen Zhang, Harold Soh*2024 · 155 citations*
19. **[Revisiting DocRED - Addressing the False Negative Problem in Relation Extraction](https://md.research.elamur.ai/free/en/papers/tan-2022-revisiting-docred-addressing-false-negative/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Qingyu Tan, Lu Xu, Lidong Bing, et al.*2022 · 151 citations*
20. **[UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/oguz-2022-unik-qa-unified-representations-structured/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Barlas Oguz, Xilun Chen, Vladimir Karpukhin, et al.*2022 · 147 citations*
21. **[Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases](https://md.research.elamur.ai/free/en/papers/cao-2021-knowledgeable-or-educated-guess-revisiting/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2021 · 141 citations*
22. [**LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks arXiv:2412.15204**Yushi Bai, Shangqing Tu, Jiajie Zhang, et al.*2024 · 135 citations*](https://md.research.elamur.ai/free/en/papers/bai-2024-longbench-v2-deeper-understanding/)
23. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering arXiv:2306.04136**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/)
24. **[KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/yu-2022-kg-fid-infusing-knowledge-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Donghan Yu, Chenguang Zhu, Yuwei Fang, et al.*2022 · 116 citations*
25. **[Entity Linking in 100 Languages](https://md.research.elamur.ai/free/en/papers/botha-2020-entity-linking-100-languages/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jan A. Botha, Zifei Shan, Daniel Gillick*2020 · 114 citations*
26. **[Can Pre-trained Vision and Language Models Answer Visual Information-Seeking Questions?](https://md.research.elamur.ai/free/en/papers/chen-2023-can-pre-trained-vision-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yang Chen, Hexiang Hu, Yi Luan, et al.*2023 · 111 citations*
27. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2024-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J Ryan, Alan Ritter, et al.*2024 · 95 citations*
28. [**Reifying RDF: What Works Well With Wikidata? SSWS 2015 (ISWC workshop), CEUR-WS Vol-1457**Daniel Hernández, Aidan Hogan, Markus Krötzsch*2015 · 88 citations*](https://md.research.elamur.ai/free/en/papers/hernandez-2015-reifying-rdf-what-works-well/)
29. **[FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2024-followbench-multi-level-fine-grained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxin Jiang, Yufei Wang, Xingshan Zeng, et al.*2024 · 86 citations*
30. **[Crawling the Internal Knowledge-Base of Language Models](https://md.research.elamur.ai/free/en/papers/cohen-2023-crawling-internal-knowledge-base-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Roi Cohen, Mor Geva, Jonathan Berant, et al.*2023 · 67 citations*
31. **[Hopping Too Late: Exploring the Limitations of Large Language Models on Multi-Hop Queries](https://md.research.elamur.ai/free/en/papers/biran-2024-hopping-too-late-exploring-limitations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eden Biran, Daniela Gottesman, Sohee Yang, et al.*2024 · 55 citations*
32. [**Halo: Estimation and Reduction of Hallucinations in Open-Source Weak Large Language Models arXiv:2308.11764**Mohamed Elaraby, Mengyin Lu, Jacob Dunn, et al.*2023 · 43 citations*](https://md.research.elamur.ai/free/en/papers/elaraby-2023-halo-estimation-reduction-hallucinations-open/)
33. **[Can Large Language Models Faithfully Express Their Intrinsic Uncertainty in Words?](https://md.research.elamur.ai/free/en/papers/yona-2024-can-large-language-models-faithfully/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Gal Yona, Roee Aharoni, Mor Geva*2024 · 40 citations*
34. [**Knowledge Card: Filling LLMs' Knowledge Gaps with Plug-in Specialized Language Models arXiv:2305.09955**Shangbin Feng, Weijia Shi, Yuyang Bai, et al.*2023 · 35 citations*](https://md.research.elamur.ai/free/en/papers/feng-2023-knowledge-card-filling-llms-knowledge/)
35. [**Knowledge Graph-Augmented Language Models for Knowledge-Grounded Dialogue Generation arXiv:2305.18846**Minki Kang, Jin Myung Kwak, Jinheon Baek, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/kang-2023-knowledge-graph-augmented-language-models/)
36. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
37. [**Adapting Multilingual LLMs to Low-Resource Languages with Knowledge Graphs via Adapters arXiv:2407.01406 · 2024.kallm-1.7**Daniil Gurgurov, Mareike Hartmann, Simon Ostermann*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/gurgurov-2024-adapting-multilingual-llms-low-resource/)
38. **[Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey](https://md.research.elamur.ai/free/en/papers/yang-2025-holistic-evaluation-large-audio-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chih-Kai Yang, Neo S. Ho, Hung-yi Lee*2025 · 17 citations*
39. **[ChronoSense: Exploring Temporal Understanding in Large Language Models with Time Intervals of Events](https://md.research.elamur.ai/free/en/papers/islakoglu-2025-chronosense-exploring-temporal-understanding-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Duygu Sezen Islakoglu, Jan-Christoph Kalo*2025 · 16 citations*
40. **[UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs' Memorization](https://md.research.elamur.ai/free/en/papers/uddin-2025-unseentimeqa-time-sensitive-question-answering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Md Nayem Uddin, Amir Saeidi, Divij Handa, et al.*2025 · 14 citations*
41. **[Integrating Transformers and Knowledge Graphs for Twitter Stance Detection](https://md.research.elamur.ai/free/en/papers/clark-2021-integrating-transformers-knowledge-graphs-twitter/) [Workshop on Noisy User-generated Text](https://md.research.elamur.ai/free/en/venues/wnut/)**Thomas Clark, Costanza Conforti, Fangyu Liu, et al.*2021 · 14 citations*
42. **[BMIKE-53: Investigating Cross-Lingual Knowledge Editing with In-Context Learning](https://md.research.elamur.ai/free/en/papers/nie-2025-bmike-53-investigating-cross-lingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ercong Nie, Bo Shao, Mingyang Wang, et al.*2025 · 12 citations*
43. **[Grounding Multilingual Multimodal LLMs With Cultural Knowledge](https://md.research.elamur.ai/free/en/papers/nyandwi-2025-grounding-multilingual-multimodal-llms-cultural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jean De Dieu Nyandwi, Yueqi Song, Simran Khanuja, et al.*2025 · 11 citations*
44. [**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/)
45. [**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/)
46. **[RGR-KBQA: Generating Logical Forms for Question Answering Using Knowledge-Graph-Enhanced Large Language Model](https://md.research.elamur.ai/free/en/papers/feng-2025-rgr-kbqa-generating-logical-forms/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Tengfei Feng, Liang He*2025 · 9 citations*
47. **[How Good is Your Wikipedia? Auditing Data Quality for Low-resource and Multilingual NLP](https://md.research.elamur.ai/free/en/papers/tatariya-2026-how-good-is-your-wikipedia/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kushal Tatariya, Artur Kulmizev, Wessel Poelman, et al.*2026 · 6 citations*
48. **[Enrich-on-Graph: Query-Graph Alignment for Complex Reasoning with LLM Enriching](https://md.research.elamur.ai/free/en/papers/li-2025-enrich-graph-query-graph-alignment/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Songze Li, Zhiqiang Liu, Zhengke Gui, et al.*2025 · 4 citations*
49. **[What Breaks Knowledge Graph based RAG? Benchmarking and Empirical Insights into Reasoning under Incomplete Knowledge](https://md.research.elamur.ai/free/en/papers/zhou-2026-what-breaks-knowledge-graph-based/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Dongzhuoran Zhou, Yuqicheng Zhu, Xiaxia Wang, et al.*2026 · 3 citations*
50. **[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*
51. **[Modelling Analogies and Analogical Reasoning: Connecting Cognitive Science Theory and NLP Research](https://md.research.elamur.ai/free/en/papers/petersen-2026-modelling-analogies-analogical-reasoning-connecting/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Molly R. Petersen, Claire E. Stevenson, Lonneke van der Plas*2026 · 1 citation*
52. **[Structured and Abstractive Reasoning on Multi-modal Relational Knowledge Images](https://md.research.elamur.ai/free/en/papers/zhang-2026-structured-abstractive-reasoning-multi-modal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yichi Zhang, Zhuo Chen, Lingbing Guo, et al.*2026 · 1 citation*
53. **[A Qualia-Based Audit of Procedural Event Annotations](https://md.research.elamur.ai/free/en/papers/rim-2026-qualia-based-audit-procedural-event/) [Workshop on Event Extraction and Understanding: Challenges and Applications](https://md.research.elamur.ai/free/en/venues/eeuca/)**Kyeongmin Rim, Marc Verhagen, James Pustejovsky*2026*
54. **[ENEIDE: A High Quality Silver Standard Dataset for Named Entity Recognition and Linking in Historical Italian](https://md.research.elamur.ai/free/en/papers/santini-2026-eneide-high-quality-silver-standard/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Cristian Santini, Sebastian Barzaghi, Paolo Sernani, et al.*2026*
55. **[EvoMemKG: An Evolvable Memory Agent for Multi-hop Knowledge Graph Reasoning](https://md.research.elamur.ai/free/en/papers/tian-2026-evomemkg-evolvable-memory-agent-multi/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shiyu Tian, Shuyue Xing, Zhuoxin Han, et al.*2026*
56. **[G-HiRel: Enhancing the Adaption to Knowledge Updating for Large Language Model Reasoning](https://md.research.elamur.ai/free/en/papers/pan-2026-g-hirel-enhancing-adaption-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yudai Pan, Jiajie Hong, Tianzhe Zhao, et al.*2026*
57. **[HistoryBankQA: Multilingual Temporal Question Answering on Historical Events](https://md.research.elamur.ai/free/en/papers/mandal-2026-historybankqa-multilingual-temporal-question-answering/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Biswadip Mandal, Anant Khandelwal, Manish Gupta*2026*
58. **[KGHaluBench: A Knowledge Graph-Based Hallucination Benchmark for Evaluating the Breadth and Depth of LLM Knowledge](https://md.research.elamur.ai/free/en/papers/robertson-2026-kghalubench-knowledge-graph-based-hallucination/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Alex Robertson, Huizhi Liang, Mahbub Gani, et al.*2026*
59. **[M³-VQA: A Benchmark for Multimodal, Multi-Entity, Multi-Hop Visual Question Answering](https://md.research.elamur.ai/free/en/papers/ma-2026-m-3-vqa-benchmark-multimodal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jiatong Ma, Longteng Guo, Yuchen Liu, et al.*2026*
60. **[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*
61. **[Subgraph-Guided Executable Logical Form Generation for Knowledge Base Question Answering](https://md.research.elamur.ai/free/en/papers/tian-2026-subgraph-guided-executable-logical-form/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yuhang Tian, Dandan Song, Zhijing Wu, et al.*2026*
62. **[TokCollate: A Comprehensive Tool for Tokenizer Evaluation and Visualization across Languages](https://md.research.elamur.ai/free/en/papers/varis-2026-tokcollate-comprehensive-tool-tokenizer-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dušan Variš, Abishek Stephen, Jindřich Libovický*2026*
63. **[Word Surprisal Correlates with Sentential Contradiction in LLMs](https://md.research.elamur.ai/free/en/papers/shi-2026-word-surprisal-correlates-sentential-contradiction/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ning Shi, Bradley Hauer, David Basil, et al.*2026*
64. **[Method for Expanding Event Commonsense Knowledge Graph Based on Large Language Models (基于大语言模型的事件常识知识图谱扩展方法)](https://md.research.elamur.ai/free/en/papers/huang-2024-method-expanding-event/) [Journal of Software](https://md.research.elamur.ai/free/en/venues/journal-of-software/)**Qiaojuan Huang (黄俏娟), Cungen Cao (曹存根), Ya Wang (王亚), 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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