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Machine Teaching (MT) is an interactive process where humans train a machine learning model by playing the role of a teacher.
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Machine Teaching: An Inverse Problem to Machine Learning and an Approach Toward Optimal Education
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Human-in-the-Loop Parsing
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Interactive Semantic Featuring for Text Classification
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”Why Should I Trust You?” Explaining the Predictions of Any Classifier
M. T Ribeiro, S Singh, and C Guestrin · 2016
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Improving Neural Machine Translation Models with Monolingual Data
R Sennrich, B Haddow, and A Birch · 2016
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Iterative Machine Teaching
W Liu, B Dai, A Humayun, et al · 2017
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Machine Teaching: A New Paradigm for Building Machine Learning Systems
P Simard, S Amershi, D Chickering, et al · 2017
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Bringing Transparency Design into Practice
M Eiband, H Schneider, M Bilandzic, et al · 2018
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GAN-based Synthetic Medical Image Augmentation for increased CNN Performance in Liver Lesion Classification
M Frid-Adar, I Diamant, E Klang, et al · 2018
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DistilBERT a distilled version of BERT: smaller, faster, cheaper and lighter
V Sanh, L Debut, J Chaumond, et al · 2019
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Taxonomy and Survey of Interpretable Machine Learning Method
S Das, N Agarwal, D Venugopal, et al · 2020
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Interactive Machine Teaching: A Human-centered Approach to Building Machine-learned Models
G Ramos, C Meek, P Simard, et al · 2020
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A Survey of Active Learning for Text Classification using Deep Neural Networks
C Schröder and A Niekler · 2020
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Learning to summarize from human feedback
N Stiennon, L Ouyang, J Wu, et al · 2020
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EDA: Easy data augmentation techniques for boosting performance on text classification tasks
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Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations
S Kobayashi · 2018
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Can Neural Machine Translation be Improved with User Feedback?
J Kreutzer, S Khadivi, E Matusov, et al · 2018
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An Overview of Machine Teaching
X Zhu, A Singla, S Zilles, et al · 2018
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BERT: Pre-training of deep bidirectional transformers for language understanding
J Devlin, M Chang, K Lee, et al · 2019
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Neural Architecture Search: A Survey
T Elsken, J Metzen, and F Hutter · 2019
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Jill Watson: A Virtual Teaching Assistant for Online Education
A Goel and L Polepeddi · 2019
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J Wei and K Zou · 2020
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HuggingFace Transformers: State-of-the-Art Natural Language Processing
T Wolf, L Debut, V Sanh, et al · 2020
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Understanding the Relationship between Interactions and Outcomes in Human-in-the-Loop Machine Learning
Y Cui, P Koppol, H Admoni, et al · 2021
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Data Augmentation Can Improve Robustness
S Rebuffi, S Gowal, D Calian, et al · 2021
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Putting Humans in the Natural Language Processing Loop: A Survey
Z Wang, D Choi, S Xu, et al · 2021
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Agent Smith: Teaching Question Answering to Jill Watson
A Goel, H Sikka, and E Gregori · 2022
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