no code implementations • LREC 2022 • Yuxiang Zhang, Hayato Yamana
The HRCA model updates the information learned from the previous relation-pair to the next relation-pair.
1 code implementation • 30 Dec 2023 • Yuki Yada, Tsuneo Matsumoto, Fuyuko Kido, Hayato Yamana
In this paper, we study interpretable dark pattern auto-detection, that is, why a particular user interface is detected as having dark patterns.
no code implementations • 6 May 2023 • Yuxiang Zhang, Junjie Wang, Xinyu Zhu, Tetsuya Sakai, Hayato Yamana
Named-entity recognition (NER) detects texts with predefined semantic labels and is an essential building block for natural language processing (NLP).
1 code implementation • 12 Nov 2022 • Yuki Yada, Jiaying Feng, Tsuneo Matsumoto, Nao Fukushima, Fuyuko Kido, Hayato Yamana
Dark patterns, which are user interface designs in online services, induce users to take unintended actions.
1 code implementation • 6 Jun 2021 • Satoru Watanabe, Hayato Yamana
The inner representation of deep neural networks (DNNs) is indecipherable, which makes it difficult to tune DNN models, control their training process, and interpret their outputs.
no code implementations • SEMEVAL 2020 • Cheng Zhang, Hayato Yamana
For subtask B, we simply use a sequence-pair BERT model, the official accuracy of which is 0. 53196 and ranks 25th out of 32.
no code implementations • 8 Sep 2020 • Takumi Ishiyama, Takuya Suzuki, Hayato Yamana
In this study, we seek to improve the classification accuracy for inference processing in a convolutional neural network (CNN) while using homomorphic encryption.