Search Results for author:
Found 4 papers, 1 papers with code
Continual Graph Convolutional Network for Text Classification
Graph convolutional network (GCN) has been successfully applied to capture global non-consecutive and long-distance semantic information for text classification.
EPiDA: An Easy Plug-in Data Augmentation Framework for High Performance Text Classification
However, to the best of our knowledge, most existing methods consider only either the diversity or the quality of augmented data, thus cannot fully mine the potential of DA for NLP.
DP-SSL: Towards Robust Semi-supervised Learning with A Few Labeled Samples
Extensive experiments on four standard SSL benchmarks show that DP-SSL can provide reliable labels for unlabeled data and achieve better classification performance on test sets than existing SSL methods, especially when only a small number of labeled samples are available.
Weakly-supervised Text Classification Based on Keyword Graph
Among them, keyword-driven methods are the mainstream where user-provided keywords are exploited to generate pseudo-labels for unlabeled texts.
