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Machine Learning
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Data Augmentation
3622 directly classified papers
Papers per year
2002: 2
2006: 1
2008: 2
2009: 1
2011: 3
2012: 3
2013: 9
2014: 8
2015: 7
2016: 35
2017: 45
2018: 108
2019: 239
2020: 329
2021: 477
2022: 518
2023: 607
2024: 561
2025: 546
2026: 121
Papers
More Diverse Dialogue Datasets via Diversity-Informed Data Collection
ACL 2020
Simulated multiple reference training improves low-resource machine translation
EMNLP 2020
Local Additivity Based Data Augmentation for Semi-supervised NER
EMNLP 2020
SSMBA: Self-Supervised Manifold Based Data Augmentation for Improving Out-of-Domain Robustness
EMNLP 2020
Named Entity Recognition for Social Media Texts with Semantic Augmentation
EMNLP 2020
Dynamic Data Selection and Weighting for Iterative Back-Translation
EMNLP 2020
DAGA: Data Augmentation with a Generation Approach for Low-resource Tagging Tasks
EMNLP 2020
SeqMix: Augmenting Active Sequence Labeling via Sequence Mixup
EMNLP 2020
The Language Interpretability Tool: Extensible, Interactive Visualizations and Analysis for NLP Models
EMNLP 2020
Improving Grammatical Error Correction with Machine Translation Pairs
EMNLP 2020
YerevaNN’s Systems for WMT20 Biomedical Translation Task: The Effect of Fixing Misaligned Sentence Pairs
EMNLP 2020
Generating Diverse Translation by Manipulating Multi-Head Attention
AAAI 2020
Partial Label Learning with Batch Label Correction
AAAI 2020
Nonlinear Mixup: Out-Of-Manifold Data Augmentation for Text Classification
AAAI 2020
Annotating Temporal Dependency Graphs via Crowdsourcing
EMNLP 2020
Adversarial Augmentation Policy Search for Domain and Cross-Lingual Generalization in Reading Comprehension
EMNLP 2020
AxCell: Automatic Extraction of Results from Machine Learning Papers
EMNLP 2020
Deep Subspace Clustering with Data Augmentation
NIPS 2020
Counterfactual Data Augmentation using Locally Factored Dynamics
NIPS 2020
Improving Generalization in Reinforcement Learning with Mixture Regularization
NIPS 2020
Reinforcement Learning with Augmented Data
NIPS 2020
GradAug: A New Regularization Method for Deep Neural Networks
NIPS 2020
Learning Invariances in Neural Networks from Training Data
NIPS 2020
RandAugment: Practical Automated Data Augmentation with a Reduced Search Space
NIPS 2020
Curriculum By Smoothing
NIPS 2020
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