--- title: "Who cites DBpedia – A Large-scale, Multilingual Knowledge…" description: "394 papers of the Elamur Research library cite «DBpedia – A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia», found in their…" canonical: "https://research.elamur.ai/free/en/papers/lehmann-2015-dbpedia-large-scale-multilingual-knowledge/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/lehmann-2015-dbpedia-large-scale-multilingual-knowledge/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [DBpedia – A Large-scale, Multilingual Knowledge…](https://md.research.elamur.ai/free/en/papers/lehmann-2015-dbpedia-large-scale-multilingual-knowledge/) / cited by # Who cites «DBpedia – A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia» 394 papers of our library cite it (of the 140,884 whose bibliographies we read) · 20 with a page here, the most cited first · [← the paper](https://md.research.elamur.ai/free/en/papers/lehmann-2015-dbpedia-large-scale-multilingual-knowledge/) 1. [**Character-level Convolutional Networks for Text Classification**Xiang Zhang, Junbo Zhao, Yann LeCun*2015 · 4,753 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2015-character-level-convolutional-networks-text/) 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. [**Multitask Prompted Training Enables Zero-Shot Task Generalization**Victor Sanh, Albert Webson, Colin Raffel, et al.*2021 · 1,577 citations*](https://md.research.elamur.ai/free/en/papers/sanh-2021-multitask-prompted-training-enables-zero/) 4. [**From Zero to Hero: On the Limitations of Zero-Shot Language Transfer with Multilingual Transformers**Anne Lauscher, Vinit Ravishankar, Ivan Vulić, et al.*2020 · 461 citations*](https://md.research.elamur.ai/free/en/papers/lauscher-2020-zero-hero-limitations-zero-shot/) 5. [**Adversarial Training Methods for Semi-Supervised Text Classification**Takeru Miyato, Andrew M. Dai, Ian Goodfellow*2016 · 416 citations*](https://md.research.elamur.ai/free/en/papers/miyato-2016-adversarial-training-methods-semi-supervised/) 6. [**Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification**Shengding Hu, Ning Ding, Huadong Wang, et al.*2022 · 360 citations*](https://md.research.elamur.ai/free/en/papers/hu-2022-knowledgeable-prompt-tuning-incorporating-knowledge/) 7. [**Symbolic Knowledge Distillation: from General Language Models to Commonsense Models**Peter West, Chandra Bhagavatula, Jack Hessel, et al.*2022 · 343 citations*](https://md.research.elamur.ai/free/en/papers/west-2022-symbolic-knowledge-distillation-general-language/) 8. [**Lessons from Natural Language Inference in the Clinical Domain**Alexey Romanov, Chaitanya Shivade*2018 · 343 citations*](https://md.research.elamur.ai/free/en/papers/romanov-2018-lessons-natural-language-inference-clinical/) 9. [**RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning**Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.*2022 · 327 citations*](https://md.research.elamur.ai/free/en/papers/deng-2022-rlprompt-optimizing-discrete-text-prompts/) 10. [**Generating Wikipedia by Summarizing Long Sequences**Peter J. Liu, Mohammad Saleh, Etienne Pot, et al.*2018 · 308 citations*](https://md.research.elamur.ai/free/en/papers/liu-2018-generating-wikipedia-summarizing-long-sequences/) 11. [**OpenPrompt: An Open-source Framework for Prompt-learning**Ning Ding, Shengding Hu, Weilin Zhao, et al.*2022 · 278 citations*](https://md.research.elamur.ai/free/en/papers/ding-2022-openprompt-open-source-framework-prompt/) 12. [**Text Classification Using Label Names Only: A Language Model Self-Training Approach**Yu Meng, Yunyi Zhang, Jiaxin Huang, et al.*2020 · 274 citations*](https://md.research.elamur.ai/free/en/papers/meng-2020-text-classification-label-names-only/) 13. [**Aya Model: An Instruction Finetuned Open-Access Multilingual Language Model**Ahmet Üstün, Viraat Aryabumi, Zheng-Xin Yong, et al.*2024 · 245 citations*](https://md.research.elamur.ai/free/en/papers/ustun-2024-aya-model-instruction-finetuned-open/) 14. [**Noisy Channel Language Model Prompting for Few-Shot Text Classification**Sewon Min, Mike Lewis, Hannaneh Hajishirzi, et al.*2021 · 238 citations*](https://md.research.elamur.ai/free/en/papers/min-2021-noisy-channel-language-model-prompting/) 15. [**Unified Demonstration Retriever for In-Context Learning**Xiaonan Li, Kai Lv, Hang Yan, et al.*2023 · 144 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-unified-demonstration-retriever-context-learning/) 16. [**We Usually Don't Like Going to the Dentist: Using Common Sense to Detect Irony on Twitter**Cynthia Van Hee, Els Lefever, Véronique Hoste*2018 · 39 citations*](https://md.research.elamur.ai/free/en/papers/hee-2018-we-usually-don-t-like/) 17. [**Pivot-based multilingual dictionary building using Wiktionary**Judit Acs*2014 · 27 citations*](https://md.research.elamur.ai/free/en/papers/acs-2014-wikt2dict-pivot/) 18. [**Reifying RDF: What Works Well With Wikidata?**Daniel Hernández, Aidan Hogan, Markus Krötzsch*2015 · 7 citations*](https://md.research.elamur.ai/free/en/papers/hernandez-2015-reifying-rdf-what-works-well/) 19. [**It's absolutely divine! Can fine-grained sentiment analysis benefit from coreference resolution?**Orphee De Clercq, Veronique Hoste*2020 · 5 citations*](https://md.research.elamur.ai/free/en/papers/clercq-2020-it-s-absolutely-divine-can/) 20. [**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/) 374 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/lehmann-2015-dbpedia-large-scale-multilingual-knowledge/) — DBpedia – A Large-scale, Multilingual Knowledge Base Extracted from Wikipedia