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Active learning is the iterative construction of a classification model through targeted labeling, enabling significant labeling cost savings.
Distilbert, a distilled version of bert: smaller, faster, cheaper and lighter
Victor Sanh, Lysandre Debut, Julien Chaumond, and Thomas Wolf. 2019 · 1910
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Neural network ensembles, cross validation and active learning
Anders Krogh and Jesper Vedelsby. 1994 · 1994
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A sequential algorithm for training text classifiers
David D. Lewis and William A. Gale. 1994 · 1994
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Minimisation of data collection by active learning
Tirthankar RayChaudhuri and Leonard G. C. Hamey. 1995 · 1995
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Less is more: Active learning with support vector machines
Greg Schohn and David Cohn. 2000 · 2000
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Toward optimal active learning through sampling estimation of error reduction
Nicholas Roy and Andrew McCallum. 2001 · 2001
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Active hidden markov models for information extraction
Tobias Scheffer, Christian Decomain, and Stefan Wrobel. 2001 · 2001
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Learning question classifiers
Xin Li and Dan Roth. 2002 · 2002
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Mining and summarizing customer reviews
Minqing Hu and Bing Liu. 2004 · 2004
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Jinghui Lu and Brian MacNamee. 2020 · 2004
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A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts
Bo Pang and Lillian Lee. 2004 · 2004
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Reducing labeling effort for structured prediction tasks
Aron Culotta and Andrew McCallum. 2005 · 2005
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Active learning to recognize multiple types of plankton
Tong Luo, Kurt Kramer, Dmitry B. Goldgof, Lawrence O. Hall, Scott Samson, Andrew Remsen, and Thomas Hopkins. 2005 · 2005
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Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales
Bo Pang and Lillian Lee. 2005 · 2005
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Multiple-instance active learning
Burr Settles, Mark Craven, and Soumya Ray. 2007 · 2007
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Entropy-based active learning for object recognition
P. Perona, A. Holub, and M. C. Burl. 2008 · 2008
Cited alongside, same era.
Efficient estimation of word representations in vector space
Tomás Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 2013 · 2013
Cited alongside, same era.
Convolutional neural networks for sentence classification
Yoon Kim. 2014 · 2014
Cited alongside, same era.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Self-adaptive hierarchical sentence model
Han Zhao, Zhengdong Lu, and Pascal Poupart. 2015 · 2015
Cited alongside, same era.
On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q. Weinberger. 2017 · 2017
Universal language model fine-tuning for text classification
Jeremy Howard and Sebastian Ruder. 2018 · 2018
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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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Practical obstacles to deploying active learning
David Lowell, Zachary C. Lipton, and Byron C. Wallace. 2019 · 2019
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Sampling bias in deep active classification: An empirical study
Ameya Prabhu, Charles Dognin, and Maneesh Singh. 2019 · 2019
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How to fine-tune BERT for text classification?
Chi Sun, Xipeng Qiu, Yige Xu, and Xuanjing Huang. 2019 · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime Carbonell, and Quoc V. Salakhutdinov, Russ R a.nd Le. 2019 · 2019
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Cited alongside, same era.
Bag of tricks for efficient text classification
Armand Joulin, Edouard Grave, Piotr Bojanowski, and Tomas Mikolov. 2017 · 2017
Cited alongside, same era.
Simple and scalable predictive uncertainty estimation using deep ensembles
Balaji Lakshminarayanan, Alexander Pritzel, and Charles Blundell. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Active discriminative text representation learning
Ye Zhang, Matthew Lease, and Byron C. Wallace. 2017 · 2017
Cited alongside, same era.
Active discriminative text representation learning
Ye Zhang, Matthew Lease, and Byron C. Wallace. 2017 · 2017
Cited alongside, same era.
Active learning for deep semantic parsing
Long Duong, Hadi Afshar, Dominique Estival, Glen Pink, Philip Cohen, and Mark Johnson. 2018 · 2018
Cited alongside, same era.
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Dynamically route hierarchical structure representation to attentive capsule for text classification
Wanshan Zheng, Zibin Zheng, Hai Wan, and Chuan Chen. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Active Learning for BERT: An Empirical Study
Liat Ein-Dor, Alon Halfon, Ariel Gera, Eyal Shnarch, Lena Dankin, Leshem Choshen, Marina Danilevsky, Ranit Aharonov, Yoav Katz, and Noam Slonim. 2020 · 2020
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Cold-start active learning through self-supervised language modeling
Michelle Yuan, Hsuan-Tien Lin, and Jordan Boyd-Graber. 2020 · 2020
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SimCSE: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen. 2021 · 2021
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Active learning by acquiring contrastive examples
Katerina Margatina, Giorgos Vernikos, Loïc Barrault, and Nikolaos Aletras. 2021 · 2021
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Cartography active learning
Mike Zhang and Barbara Plank. 2021 · 2021
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Small-Text: Active learning for text classification in python
Christopher Schröder, Lydia Müller, Andreas Niekler, and Martin Potthast. 2022 · 2022
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