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Data Augmentation

429 directly classified papers

Papers per year

Papers

Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis IJCNLP 2021
Changes in European Solidarity Before and During COVID-19: Evidence from a Large Crowd- and Expert-Annotated Twitter Dataset IJCNLP 2021
Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection IJCNLP 2021
Data Augmentation for Text Generation Without Any Augmented Data IJCNLP 2021
LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification IJCNLP 2021
BERT Goes Brrr: A Venture Towards the Lesser Error in Classifying Medical Self-Reporters on Twitter NAACL 2021
UoB at ProfNER 2021: Data Augmentation for Classification Using Machine Translation NAACL 2021
Interpretable Minority Synthesis for Imbalanced Classification IJCAI 2021
Time Series Data Augmentation for Deep Learning: A Survey IJCAI 2021
Towards Rotation Invariance in Object Detection ICCV 2021
Data Augmentation Methods for End-to-End Speech Recognition on Distant-Talk Scenarios INTERSPEECH 2021
Semi-Supervision in ASR: Sequential MixMatch and Factorized TTS-Based Augmentation INTERSPEECH 2021
On-the-Fly Aligned Data Augmentation for Sequence-to-Sequence ASR INTERSPEECH 2021
Text Augmentation for Language Models in High Error Recognition Scenario INTERSPEECH 2021
Exploring Inspiration Sets in a Data Programming Pipeline for Product Moderation ACL 2021
Exploring the Efficacy of Automatically Generated Counterfactuals for Sentiment Analysis ACL 2021
Learning from the Worst: Dynamically Generated Datasets to Improve Online Hate Detection ACL 2021
Data Augmentation for Text Generation Without Any Augmented Data ACL 2021
Robustness Testing of Language Understanding in Task-Oriented Dialog ACL 2021
LearnDA: Learnable Knowledge-Guided Data Augmentation for Event Causality Identification ACL 2021
Reinforced Counterfactual Data Augmentation for Dual Sentiment Classification EMNLP 2021
How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs? EMNLP 2021
Discovering the Unknown Knowns: Turning Implicit Knowledge in the Dataset into Explicit Training Examples for Visual Question Answering EMNLP 2021
Simple Conversational Data Augmentation for Semi-supervised Abstractive Dialogue Summarization EMNLP 2021
Multi-Sentence Resampling: A Simple Approach to Alleviate Dataset Length Bias and Beam-Search Degradation EMNLP 2021