425 citations · 956 across the 28 of their papers we have counts for
7 papers · 1 filter
Expressions Causing Differences in Emotion Recognition in Social Networking Service Documents
Tsubasa Nakagawa, Shunsuke Kitada, Hitoshi Iyatomi
It is often difficult to correctly infer a writer's emotion from text exchanged online, and differences in recognition between writers and readers can be problematic. In this paper…
Making Attention Mechanisms More Robust and Interpretable with Virtual Adversarial Training
Shunsuke Kitada, Hitoshi Iyatomi
Although attention mechanisms have become fundamental components of deep learning models, they are vulnerable to perturbations, which may degrade the prediction performance and mod…
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.…
Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creative
Shunsuke Kitada, Hitoshi Iyatomi, Yoshifumi Seki
Accurately predicting conversions in advertisements is generally a challenging task, because such conversions do not occur frequently. In this paper, we propose a new framework to…