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Obtaining large-scale annotated data for NLP tasks in the scientific domain is challenging and expensive.
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. 2019 · 1901
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ScispaCy: Fast and robust models for biomedical natural language processing
Mark Neumann, Daniel King, Iz Beltagy, and Waleed Ammar. 2019 · 1902
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Clinicalbert: Modeling clinical notes and predicting hospital readmission
Kexin Huang, Jaan Altosaar, and Rajesh Ranganath. 2019 · 1904
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GENIA corpus - a semantically annotated corpus for bio-textmining
Jin-Dong Kim, Tomoko Ohta, Yuka Tateisi, and Jun’ichi Tsujii. 2003 · 2003
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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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Automatic classification of sentences to support evidence based medicine
Su Kim, David Martínez, Lawrence Cavedon, and Lars Yencken. 2011 · 2011
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NCBI disease corpus: A resource for disease name recognition and concept normalization
Rezarta Islamaj Dogan, Robert Leaman, and Zhiyong Lu. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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An overview of microsoft academic service (MAS) and applications
Arnab Sinha, Zhihong Shen, Yang Song, Hao Ma, Darrin Eide, Bo-June Paul Hsu, and Kuansan Wang. 2015 · 2015
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Mimic-iii, a freely accessible critical care database
Alistair E. W. Johnson, Tom J. Pollard aand Lu Shen, Liwei H. Lehman, Mengling Feng, Mohammad Ghassemi, Benjamin Moody, Peter Szolovits, Leo Anthony Celi, , and Roger G. Mark. 2016 · 2016
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ChemProt-3.0: a global chemical biology diseases mapping
Jens Kringelum, Sonny Kim Kjærulff, Søren Brunak, Ole Lund, Tudor I. Oprea, and Olivier Taboureau. 2016 · 2016
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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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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Lukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Gregory S. Corrado, Macduff Hughes, and Jeffrey Dean. 2016 · 2016
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Deep biaffine attention for neural dependency parsing
Timothy Dozat and Christopher D. Manning. 2017 · 2017
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Multi-task identification of entities, relations, and coreference for scientific knowledge graph construction
Yi Luan, Luheng He, Mari Ostendorf, and Hannaneh Hajishirzi. 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 James Marshall, Ani Nenkova, and Byron C. Wallace. 2018 · 2018
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Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke S. Zettlemoyer. 2018 · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever. 2018 · 2018
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CollaboNet: collaboration of deep neural networks for biomedical named entity recognition
Wonjin Yoon, Chan Ho So, Jinhyuk Lee, and Jaewoo Kang. 2018 · 2018
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alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Matt Gardner, Joel Grus, Mark Neumann, Oyvind Tafjord, Pradeep Dasigi, Nelson F. Liu, Matthew Peters, Michael Schmitz, and Luke S. Zettlemoyer. 2017 · 2017
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Optimal hyperparameters for deep lstm-networks for sequence labeling tasks
Nils Reimers and Iryna Gurevych. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Construction of the literature graph in semantic scholar
Waleed Ammar, Dirk Groeneveld, Chandra Bhagavatula, Iz Beltagy, Miles Crawford, Doug Downey, Jason Dunkelberger, Ahmed Elgohary, Sergey Feldman, Vu Ha, Rodney Kinney, Sebastian Kohlmeier, Kyle Lo, Tyler Murray, Hsu-Han Ooi, Matthew Peters, Joanna Power, Sam Skjonsberg, Lucy Lu Wang, Chris Wilhelm, Zheng Yuan, Madeleine van Zuylen, and Oren Etzioni. 2018 · 2018
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Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
Cited alongside, same era.
Measuring the evolution of a scientific field through citation frames
David Jurgens, Srijan Kumar, Raine Hoover, Daniel A. McFarland, and Daniel Jurafsky. 2018 · 2018
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Publicly available clinical bert embeddings
Emily Alsentzer, John R. Murphy, Willie Boag, Wei-Hung Weng, Di Jin, Tristan Naumann, and Matthew B. A. McDermott. 2019 · 2019
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Structural scaffolds for citation intent classification in scientific publications
Arman Cohan, Waleed Ammar, Madeleine van Zuylen, and Field Cady. 2019 · 2019
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TPUs vs GPUs for Transformers (BERT)
Tim Dettmers. 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
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From pos tagging to dependency parsing for biomedical event extraction
Dat Quoc Nguyen and Karin M. Verspoor. 2019 · 2019
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