29 citations · 67 across the 17 of their papers we have counts for
3 papers · 1 filter
Text Classification through Glyph-aware Disentangled Character Embedding and Semantic Sub-character Augmentation
Takumi Aoki, Shunsuke Kitada, Hitoshi Iyatomi
We propose a new character-based text classification framework for non-alphabetic languages, such as Chinese and Japanese. Our framework consists of a variational character encoder…
Attention Meets Perturbations: Robust and Interpretable Attention with Adversarial Training
Shunsuke Kitada, Hitoshi Iyatomi
Although attention mechanisms have been applied to a variety of deep learning models and have been shown to improve the prediction performance, it has been reported to be vulnerabl…
AraDIC: Arabic Document Classification using Image-Based Character Embeddings and Class-Balanced Loss
Mahmoud Daif, Shunsuke Kitada, Hitoshi Iyatomi
Classical and some deep learning techniques for Arabic text classification often depend on complex morphological analysis, word segmentation, and hand-crafted feature engineering.…