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Language model (LM) pretraining can learn various knowledge from text corpora, helping downstream tasks.
Ernie: Enhanced language representation with informative entities
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Pancreatic cancer and thromboembolic disease, 150 years after trousseau
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Extraction of relations between genes and diseases from text and large-scale data analysis: implications for translational research
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Automatic semantic classification of scientific literature according to the hallmarks of cancer
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Reading wikipedia to answer open-domain questions
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Searchqa: A new q&a dataset augmented with context from a search engine
Matthew Dunn, Levent Sagun, Mike Higgins, V Ugur Guney, Volkan Cirik, and Kyunghyun Cho. 2017 · 2017
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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
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Overview of the biocreative vi chemical-protein interaction track
Martin Krallinger, Obdulia Rabal, Saber A Akhondi, Martın Pérez Pérez, Jesús Santamaría, Gael Pérez Rodríguez, Georgios Tsatsaronis, and Ander Intxaurrondo. 2017 · 2017
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Biosses: a semantic sentence similarity estimation system for the biomedical domain
Gizem Soğancıoğlu, Hakime Öztürk, and Arzucan Özgür. 2017 · 2017
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Specter: Document-level representation learning using citation-informed transformers
Arman Cohan, Sergey Feldman, Iz Beltagy, Doug Downey, and Daniel S Weld. 2020 · 2020
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Realm: Retrieval-augmented language model pre-training
Kelvin Guu, Kenton Lee, Zora Tung, Panupong Pasupat, and Ming-Wei Chang. 2020 · 2020
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Bin He, Di Zhou, Jinghui Xiao, Xin Jiang, Qun Liu, Nicholas Jing Yuan, and Tong Xu. 2020 · 2020
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Spanbert: Improving pre-training by representing and predicting spans
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Newsqa: A machine comprehension dataset
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Adina Williams, Nikita Nangia, and Samuel R Bowman. 2017 · 2017
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Graph-based neural multi-document summarization
Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan, and Dragomir Radev. 2017 · 2017
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Content-based citation recommendation
Chandra Bhagavatula, Sergey Feldman, Russell Power, and Waleed Ammar. 2018 · 2018
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A corpus with multi-level annotations of patients, interventions and outcomes to support language processing for medical literature
Benjamin Nye, Junyi Jessy Li, Roma Patel, Yinfei Yang, Iain J Marshall, Ani Nenkova, and Byron C Wallace. 2018 · 2018
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Hotpotqa: A dataset for diverse, explainable multi-hop question answering
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Exploiting citation knowledge in personalised recommendation of recent scientific publications
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Unifiedqa: Crossing format boundaries with a single qa system
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Biobert: a pre-trained biomedical language representation model for biomedical text mining
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Exploring the limits of transfer learning with a unified text-to-text transformer
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Towards controllable biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng. 2020 · 2020
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Colake: Contextualized language and knowledge embedding
Tianxiang Sun, Yunfan Shao, Xipeng Qiu, Qipeng Guo, Yaru Hu, Xuan-Jing Huang, and Zheng Zhang. 2020 · 2020
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2020 · 2020
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Htlm: Hyper-text pre-training and prompting of language models
Armen Aghajanyan, Dmytro Okhonko, Mike Lewis, Mandar Joshi, Hu Xu, Gargi Ghosh, and Luke Zettlemoyer. 2021 · 2021
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, and Percy Liang. 2021 · 2021
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Cross-document language modeling
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Wikipedia entities as rendezvous across languages: Grounding multilingual language models by predicting wikipedia hyperlinks
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Making pre-trained language models better few-shot learners
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What disease does this patient have? a large-scale open domain question answering dataset from medical exams
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The inductive bias of in-context learning: Rethinking pretraining example design
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Pre-training for ad-hoc retrieval: Hyperlink is also you need
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Weakly supervised pre-training for multi-hop retriever
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