13 citations · 24 across the 12 of their papers we have counts for
13 papers
Kanbun-LM: Reading and Translating Classical Chinese in Japanese Methods by Language Models
Hao Wang, Hirofumi Shimizu, Daisuke Kawahara
Recent studies in natural language processing (NLP) have focused on modern languages and achieved state-of-the-art results in many tasks. Meanwhile, little attention has been paid…
Grounding in social media: An approach to building a chit-chat dialogue model
Ritvik Choudhary, Daisuke Kawahara
Building open-domain dialogue systems capable of rich human-like conversational ability is one of the fundamental challenges in language generation. However, even with recent advan…
Building a Personalized Dialogue System with Prompt-Tuning
Tomohito Kasahara, Daisuke Kawahara, Nguyen Tung +3
Dialogue systems without consistent responses are not fascinating. In this study, we build a dialogue system that can respond based on a given character setting (persona) to bring…
Generate, Evaluate, and Select: A Dialogue System with a Response Evaluator for Diversity-Aware Response Generation
Ryoma Sakaeda, Daisuke Kawahara
We aim to overcome the lack of diversity in responses of current dialogue systems and to develop a dialogue system that is engaging as a conversational partner. We propose a genera…
Building a Dialogue Corpus Annotated with Expressed and Experienced Emotions
Tatsuya Ide, Daisuke Kawahara
In communication, a human would recognize the emotion of an interlocutor and respond with an appropriate emotion, such as empathy and comfort. Toward developing a dialogue system w…
Multi-Task Learning of Generation and Classification for Emotion-Aware Dialogue Response Generation
Tatsuya Ide, Daisuke Kawahara
For a computer to naturally interact with a human, it needs to be human-like. In this paper, we propose a neural response generation model with multi-task learning of generation an…
Minimize Exposure Bias of Seq2Seq Models in Joint Entity and Relation Extraction
Ranran Haoran Zhang, Qianying Liu, Aysa Xuemo Fan +5
Joint entity and relation extraction aims to extract relation triplets from plain text directly. Prior work leverages Sequence-to-Sequence (Seq2Seq) models for triplet sequence gen…
Reverse Operation based Data Augmentation for Solving Math Word Problems
Qianying Liu, Wenyu Guan, Sujian Li +3
Automatically solving math word problems is a critical task in the field of natural language processing. Recent models have reached their performance bottleneck and require more hi…
A System for Worldwide COVID-19 Information Aggregation
Akiko Aizawa, Frederic Bergeron, Junjie Chen +26
The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education. Meanwhil…
Emotion helps Sentiment: A Multi-task Model for Sentiment and Emotion Analysis
Abhishek Kumar, Asif Ekbal, Daisuke Kawahra +1
In this paper, we propose a two-layered multi-task attention based neural network that performs sentiment analysis through emotion analysis. The proposed approach is based on Bidir…
Knowledge-enriched Two-layered Attention Network for Sentiment Analysis
Abhishek Kumar, Daisuke Kawahara, Sadao Kurohashi
We propose a novel two-layered attention network based on Bidirectional Long Short-Term Memory for sentiment analysis. The novel two-layered attention network takes advantage of th…
Neural Adversarial Training for Semi-supervised Japanese Predicate-argument Structure Analysis
Shuhei Kurita, Daisuke Kawahara, Sadao Kurohashi
Japanese predicate-argument structure (PAS) analysis involves zero anaphora resolution, which is notoriously difficult. To improve the performance of Japanese PAS analysis, it is s…
Reading Comprehension using Entity-based Memory Network
Xun Wang, Katsuhito Sudoh, Masaaki Nagata +3
This paper introduces a novel neural network model for question answering, the \emph{entity-based memory network}. It enhances neural networks' ability of representing and calculat…