Research ▸ Projects
Overview
Proposal For Project Page
Individual projects
Explainable Question Answering
Recent advances in Deep Learning have a large impact on NLP, resulting in more accurate NLP systems. However, for the systems to be more robust for unseen input texts, it is crucial for the systems to logically come up with an answer. Furthermore, when the systems are deployed in the real world, it is required for them to explain their own decision as well as answer given questions. In this project, we explore: How can we design such a computational model to do this? How can we train such a model with a machine learning algorithm? How do we imitate human reasoning?
Related papers: Inoue et al. EMNLP2021, 井之上2021
Linguistic Resources for Natural Language Understanding
To objectively measure the progress of research, we need a quantitative evaluation measure indicating the quality of our models. Our research questions include: On what condition can we say the model has successfully read between the lines? How can we quantitatively measure it? Can we create such a benchmark dataset at scale?
Related papers: Inoue et al. ACL2020, 井之上2020
Argumentation Analysis and Assessment
When we write argumentative texts (e.g. essays), we usually leave background knowledge that we expect the reader to have implicit. For machines to fully understand such texts, it is crucial to auto-complete such background knowledge. We study the problem of analyzing argumentative texts as one important application of our technology. The research questions here include: How can we recognize a relationship between claims and premises? How can we assess argumentative texts and recognize their weaknesses? What part of the texts should be revised to strengthen the argument?
Related papers: Singh et al. ArgMin2021, Mim et al. LREC2022, Singh et al. LREC2022, Naito et al. LREC2022, 谷口ら2021 (see 第7章)
Grants
- 井之上 直也 (PI). 人々が頼りたくなる自己批判的思考力を備えた言語処理機構. JST 2023年度 創発的研究支援事業, 2024/10-2028/03.
- 井之上 直也 (PI). 自己認識的に推論ができる信頼性の高いAIの研究. 中島国際交流財団 日本人独立研究者始動助成金, 2024/04-2027/03, 5,000,000JPY.
- Naoya Inoue (PI). Developing Flexible Inference Mechanism by Embedding Causality Knowledge into Continuous Space (事象間関係知識の連続空間への埋め込みによる柔軟な推論機構の開発). Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (KAKENHI 若手研究). 2019/4-2020/3, 2022/6/1-2024/3, 4,160,000JPY. 19K20332
- Kentaro Inui, Chihiro Nakagawa, and Naoya Inoue. Deep Modeling of Argumentation and its Application to Argumentative Feedback System (深い論述理解の計算モデリングと論述学習支援への応用). Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (KAKENHI 基盤A). Co-investigator. 22H00524. 2022/4-2027/3. 22H00524
- Hiroki Ouchi. 文章中の人物の移動軌跡を実世界の地図上に接地するための基礎研究とその応用. Japan Society for the Promotion of Science (JSPS) Grants-in-Aid for Scientific Research (KAKENHI 基盤B). 研究協力者. 2022/4-2025/3. 13,910,000JPY. 22H03648
Past grants can be found here.