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Found 4 papers, 1 papers with code
Importance Guided Data Augmentation for Neural-Based Code Understanding
In this paper, we introduce a general data augmentation framework, GenCode, to enhance the training of code understanding models.
Boosting Source Code Learning with Data Augmentation: An Empirical Study
The next era of program understanding is being propelled by the use of machine learning to solve software problems.
On the Effectiveness of Hybrid Pooling in Mixup-Based Graph Learning for Language Processing
Graph neural network (GNN)-based graph learning has been popular in natural language and programming language processing, particularly in text and source code classification.
MIXCODE: Enhancing Code Classification by Mixup-Based Data Augmentation
Data augmentation has been a popular approach to supplement training data in domains such as computer vision and NLP.
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