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Pre-trained language models (LMs) have become ubiquitous in solving various natural language processing (NLP) tasks.
The unified medical language system (umls): integrating biomedical terminology
Olivier Bodenreider. 2004 · 2004
Earlier work this paper cites.
Best: next-generation biomedical entity search tool for knowledge discovery from biomedical literature
Sunwon Lee, Donghyeon Kim, Kyubum Lee, Jaehoon Choi, Seongsoon Kim, Minji Jeon, Sangrak Lim, Donghee Choi, Sunkyu Kim, Aik-Choon Tan, et al. 2016 · 2016
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Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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SciBERT: A pretrained language model for scientific text
Iz Beltagy, Kyle Lo, and Arman Cohan. 2019 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Earlier work this paper cites.
Language models as knowledge bases?
Fabio Petroni, Tim Rocktäschel, Sebastian Riedel, Patrick Lewis, Anton Bakhtin, Yuxiang Wu, and Alexander Miller. 2019 · 2019
Earlier work this paper cites.
Wikidata: A large-scale collaborative ontological medical database
Houcemeddine Turki, Thomas Shafee, Mohamed Ali Hadj Taieb, Mohamed Ben Aouicha, Denny Vrandečić, Diptanshu Das, and Helmi Hamdi. 2019 · 2019
Cited alongside, same era.
X-FACTR: Multilingual factual knowledge retrieval from pretrained language models
Zhengbao Jiang, Antonios Anastasopoulos, Jun Araki, Haibo Ding, and Graham Neubig. 2020a · 2020
Cited alongside, same era.
Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2020 · 2020
Cited alongside, same era.
Pretrained language models for biomedical and clinical tasks: Understanding and extending the state-of-the-art
Patrick Lewis, Myle Ott, Jingfei Du, and Veselin Stoyanov. 2020 · 2020
Cited alongside, same era.
E-BERT: Efficient-yet-effective entity embeddings for BERT
Nina Poerner, Ulli Waltinger, and Hinrich Schütze. 2020 · 2020
Cited alongside, same era.
Biomedical entity representations with synonym marginalization
Mujeen Sung, Hwisang Jeon, Jinhyuk Lee, and Jaewoo Kang. 2020 · 2020
Later among the works it cites.
Science forum: Wikidata as a knowledge graph for the life sciences
Andra Waagmeester, Gregory Stupp, Sebastian Burgstaller-Muehlbacher, Benjamin M Good, Malachi Griffith, Obi L Griffith, Kristina Hanspers, Henning Hermjakob, Toby S Hudson, Kevin Hybiske, et al. 2020 · 2020
Later among the works it cites.
Knowledgeable or educated guess? revisiting language models as knowledge bases
Boxi Cao, Hongyu Lin, Xianpei Han, Le Sun, Lingyong Yan, Meng Liao, Tong Xue, and Jin Xu. 2021 · 2021
Closest in time.
Comparative Toxicogenomics Database (CTD): update 2021
Allan Peter Davis, Cynthia J Grondin, Robin J Johnson, Daniela Sciaky, Jolene Wiegers, Thomas C Wiegers, and Carolyn J Mattingly. 2020 · 2021
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Factual probing is [MASK]: Learning vs. learning to recall
Zexuan Zhong, Dan Friedman, and Danqi Chen. 2021 · 2021
Closest in time.
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AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, and Sameer Singh. 2020 · 2020
Cited alongside, same era.
How can we know what language models know?
Zhengbao Jiang, Frank F. Xu, Jun Araki, and Graham Neubig. 2020b
Cited in the paper.