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In recent years, large language models (LLMs), such as GPTs, have attained great impact worldwide.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
Earlier work this paper cites.
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Albert: A lite bert for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2019 · 1909
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Tacred revisited: A thorough evaluation of the tacred relation extraction task
Christoph Alt, Aleksandra Gabryszak, and Leonhard Hennig. 2020 · 2004
Earlier work this paper cites.
The unified medical language system (umls): integrating biomedical terminology
Olivier Bodenreider. 2004 · 2004
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Introduction to the bio-entity recognition task at jnlpba
Nigel Collier and Jin-Dong Kim. 2004 · 2004
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Overview of biocreative ii gene mention recognition
Larry Smith, Lorraine K Tanabe, Cheng-Ju Kuo, I Chung, Chun-Nan Hsu, Yu-Shi Lin, Roman Klinger, Christoph M Friedrich, Kuzman Ganchev, Manabu Torii, et al. 2008 · 2008
Earlier work this paper cites.
Tagme: on-the-fly annotation of short text fragments (by wikipedia entities)
P. Ferragina and U. Scaiella. 2010a · 2010
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Ncbi disease corpus: a resource for disease name recognition and concept normalization
Rezarta Islamaj Doğan, Robert Leaman, and Zhiyong Lu. 2014 · 2014
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Biocreative v cdr task corpus: a resource for chemical disease relation extraction
Jiao Li, Yueping Sun, Robin J Johnson, Daniela Sciaky, Chih-Hsuan Wei, Robert Leaman, Allan Peter Davis, Carolyn J Mattingly, Thomas C Wiegers, and Zhiyong Lu. 2016 · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Cn-dbpedia: A never-ending chinese knowledge extraction system
Bo Xu, Yong Xu, Jiaqing Liang, Chenhao Xie, Bin Liang, Wanyun Cui, and Yanghua Xiao. 2017 · 2017
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Position-aware attention and supervised data improve slot filling
Yuhao Zhang, Victor Zhong, Danqi Chen, Gabor Angeli, and Christopher D. Manning. 2017 · 2017
Earlier work this paper cites.
Ultra-fine entity typing
Eunsol Choi, Omer Levy, Yejin Choi, and Luke Zettlemoyer. 2018 · 2018
Earlier work this paper cites.
Investigating entity knowledge in bert with simple neural end-to-end entity linking
Samuel Broscheit. 2019 · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
English wordnet 2019–an open-source wordnet for english
John P McCrae, Alexandre Rademaker, Francis Bond, Ewa Rudnicka, and Christiane Fellbaum. 2019 · 2019
Cited alongside, same era.
Knowledge enhanced contextual word representations
Matthew E. Peters, Mark Neumann, Robert L Logan, Roy Schwartz, Vidur Joshi, Sameer Singh, and Noah A. Smith. 2019 · 2019
Cited alongside, same era.
Wic: the word-in-context dataset for evaluating context-sensitive meaning representations
Mohammad Taher Pilehvar and Jose Camacho-Collados. 2019 · 2019
Cited alongside, same era.
Re-tacred: Addressing shortcomings of the tacred dataset
George Stoica, Emmanouil Antonios Platanios, and Barnabás Póczos. 2021 · 2021
Later among the works it cites.
Cokebert: Contextual knowledge selection and embedding towards enhanced pre-trained language models
Yusheng Su, Xu Han, Zhengyan Zhang, Yankai Lin, Peng Li, Zhiyuan Liu, Jie Zhou, and Maosong Sun. 2021 · 2021
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K-adapter: Infusing knowledge into pre-trained models with adapters
Ruize Wang, Duyu Tang, Nan Duan, Zhongyu Wei, Xuan-Jing Huang, Jianshu Ji, Guihong Cao, Daxin Jiang, and Ming Zhou. 2021a · 2021
Later among the works it cites.
Improving biomedical pretrained language models with knowledge
Zheng Yuan, Yijia Liu, Chuanqi Tan, Songfang Huang, and Fei Huang. 2021 · 2021
Later among the works it cites.
Drop redundant, shrink irrelevant: Selective knowledge injection for language pretraining
Ningyu Zhang, Shumin Deng, Xu Cheng, Xi Chen, Yichi Zhang, Wei Zhang, Huajun Chen, and Hangzhou Innovation Center. 2021 · 2021
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Bin He, Di Zhou, Jinghui Xiao, Xin Jiang, Qun Liu, Nicholas Jing Yuan, and Tong Xu. 2020 · 2020
Cited alongside, same era.
How can we know what language models know?
Zhengbao Jiang, Frank F Xu, Jun Araki, and Graham Neubig. 2020 · 2020
Cited alongside, same era.
Sentilare: Sentiment-aware language representation learning with linguistic knowledge
Pei Ke, Haozhe Ji, Siyang Liu, Xiaoyan Zhu, and Minlie Huang. 2020 · 2020
Cited alongside, same era.
K-bert: Enabling language representation with knowledge graph
Weijie Liu, Peng Zhou, Zhe Zhao, Zhiruo Wang, Qi Ju, Haotang Deng, and Ping Wang. 2020 · 2020
Cited alongside, same era.
Colake: Contextualized language and knowledge embedding
Tianxiang Sun, Yunfan Shao, Xipeng Qiu, Qipeng Guo, Yaru Hu, Xuan-Jing Huang, and Zheng Zhang. 2020 · 2020
Cited alongside, same era.
LUKE: Deep contextualized entity representations with entity-aware self-attention
Ikuya Yamada, Akari Asai, Hiroyuki Shindo, Hideaki Takeda, and Yuji Matsumoto. 2020 · 2020
Cited alongside, same era.
ERNIE: Enhanced language representation with informative entities
Zhengyan Zhang, Xu Han, Zhiyuan Liu, Xin Jiang, Maosong Sun, and Qun Liu. 2019 · 2020
Cited alongside, same era.
Knowledge-augmented language models for cause-effect relation classification
Pedram Hosseini, David A Broniatowski, and Mona T Diab. 2022 · 2022
Later among the works it cites.
What has been enhanced in my knowledge-enhanced language model?
Yifan Hou, Guoji Fu, and Mrinmaya Sachan. 2022 · 2022
Later among the works it cites.
Survey of hallucination in natural language generation
ZIWEI JI, NAYEON LEE, RITA FRIESKE, TIEZHENG YU, DAN SU, YAN XU, and ETSUKO ISHII. 2022 · 2022
Later among the works it cites.
How pre-trained language models capture factual knowledge? a causal-inspired analysis
Shaobo Li, Xiaoguang Li, Lifeng Shang, Zhenhua Dong, Cheng-Jie Sun, Bingquan Liu, Zhenzhou Ji, Xin Jiang, and Qun Liu. 2022 · 2022
Later among the works it cites.
Kelm: Knowledge enhanced pre-trained language representations with message passing on hierarchical relational graphs
Yinquan Lu, Haonan Lu, Guirong Fu, and Qun Liu. 2022 · 2022
Later among the works it cites.
A simple but effective pluggable entity lookup table for pre-trained language models
Deming Ye, Yankai Lin, Peng Li, Maosong Sun, and Zhiyuan Liu. 2022 · 2022
Later among the works it cites.
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al. 2023 · 2023
Closest in time.
Benchmarking large language models on cmexam – a comprehensive chinese medical exam dataset
Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, and Michael Lingzhi Li. 2023 · 2023
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Pmc-llama: Further finetuning llama on medical papers
Chaoyi Wu, Xiaoman Zhang, Ya Zhang, Yanfeng Wang, and Weidi Xie. 2023 · 2023
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