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We address the problem of calibrating prediction confidence for output entities of interest in natural language processing (NLP) applications.
Biobert: pre-trained biomedical language representation model for biomedical text mining
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A simple baseline for bayesian uncertainty in deep learning
Wesley Maddox, Timur Garipov, Pavel Izmailov, Dmitry Vetrov, and Andrew Gordon Wilson. 2019 · 1902
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Calibration of encoder decoder models for neural machine translation
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Superglue: A stickier benchmark for general-purpose language understanding systems
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Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
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Transformers: State-of-the-art natural language processing
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A method for estimating the probability of adverse drug reactions
Cláudio A Naranjo, Usoa Busto, Edward M Sellers, P Sandor, I Ruiz, EA Roberts, E Janecek, C Domecq, and DJ Greenblatt. 1981 · 1981
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The penn treebank: annotating predicate argument structure
Mitchell Marcus, Grace Kim, Mary Ann Marcinkiewicz, Robert MacIntyre, Ann Bies, Mark Ferguson, Karen Katz, and Britta Schasberger. 1994 · 1994
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Probabilistic outputs for support vector machines and comparison to regularized likelihood methods
J Platt. 2000 · 2000
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Greedy function approximation: a gradient boosting machine
Jerome H Friedman. 2001 · 2001
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Introduction to the conll-2003 shared task: Language-independent named entity recognition
Erik F Sang and Fien De Meulder. 2003 · 2003
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Scalable training of L1-regularized log-linear models
Galen Andrew and Jianfeng Gao. 2007 · 2007
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Reliability, sufficiency, and the decomposition of proper scores
Jochen Bröcker. 2009 · 2009
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Bayesian learning via stochastic gradient langevin dynamics
Max Welling and Yee W Teh. 2011 · 2011
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Calibrated structured prediction
Volodymyr Kuleshov and Percy S Liang. 2015 · 2015
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Obtaining well calibrated probabilities using bayesian binning
Mahdi Pakdaman Naeini, Gregory Cooper, and Milos Hauskrecht. 2015 · 2015
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Posterior calibration and exploratory analysis for natural language processing models
Khanh Nguyen and Brendan O’Connor. 2015 · 2015
Confidence modeling for neural semantic parsing
Li Dong, Chris Quirk, and Mirella Lapata. 2018 · 2018
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Trainable calibration measures for neural networks from kernel mean embeddings
Aviral Kumar, Sunita Sarawagi, and Ujjwal Jain. 2018 · 2018
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Predictive uncertainty estimation via prior networks
Andrey Malinin and Mark Gales. 2018 · 2018
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emrqa: A large corpus for question answering on electronic medical records
Anusri Pampari, Preethi Raghavan, Jennifer Liang, and Jian Peng. 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 Zettlemoyer. 2018 · 2018
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Uncertainty in deep learning
Yarin Gal. 2016 · 2016
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani. 2016 · 2016
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger. 2017 · 2017
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Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Know what you don’t know: Unanswerable questions for squad
Pranav Rajpurkar, Robin Jia, and Percy Liang. 2018 · 2018
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A scalable laplace approximation for neural networks
Hippolyt Ritter, Aleksandar Botev, and David Barber. 2018 · 2018
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Clinical concept extraction with contextual word embedding
Henghui Zhu, Ioannis Ch Paschalidis, and Amir Tahmasebi. 2018 · 2018
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Overview of the first natural language processing challenge for extracting medication, indication, and adverse drug events from electronic health record notes (made 1.0)
Abhyuday Jagannatha, Feifan Liu, Weisong Liu, and Hong Yu. 2019 · 2019
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Fine-tuning bidirectional encoder representations from transformers (bert)–based models on large-scale electronic health record notes: An empirical study
Fei Li, Yonghao Jin, Weisong Liu, Bhanu Pratap Singh Rawat, Pengshan Cai, and Hong Yu. 2019 · 2019
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Detection of adverse drug reaction mentions in tweets using elmo
Sarah Sarabadani. 2019 · 2019
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