李 想 Xiang Li
反実機械学習と説明可能なAIに関する研究に従事.
IEEE Student Member.電子情報通信学会 学生員.
E-mail: xiang_li[at]lmd.ist.hokudai.ac.jp
Biography
- 2023/10 ~ 2025/09 Hokkaido University, M.S. in Information Science
- 2023/04 ~ 2023/09 Hokkaido University, Research Student
- 2018/09 ~ 2022/06 Shandong University, B.S. in Software Engineering
Publication
Journal
- Xiang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “Enhancing classification models with sophisticated counterfactual images,” IEEE Open Journal of Signal Processing, 2025. (Under review)
International Conference
- Xiang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “Enhanced framework for generating counterfactual images with sophisticated caption and inversion-free image editing,” International Workshop on Advanced Image Technology (IWAIT), 2025. (Accepted)
- Xiang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “Reinforcing pre-trained models using counterfactual images,” IEEE International Conference on Image Processing (ICIP), pp. 486-492, 2024. [arXiv] [Paper]
- Xiang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “Improving visual counterfactual explanation models for image classification via CLIP,” IEEE Global Conference on Consumer Electronics (GCCE), pp. 390-391, 2023. [Paper]
Domestic Conference
- Xiang Li, Ren Togo, Keisuke Maeda, Takahiro Ogawa, Miki Haseyama, “Strategic classification model reinforcement: Introducing language-guided counterfactual images to identify and address classification weaknesses,” Meeting on Image Recognition and Understanding (MIRU), pp. 1-5, 2024.
- 李 想, 藤後 廉, 前田 圭介, 小川 貴弘, 長谷山 美紀, “視覚反実仮想機械学習モデルにおける精度向上に関する一検討 – 特徴抽出モデルが精度に与える影響の検証 –,” 令和5年度 電気・情報関係学会北海道支部連合大会, pp. 1-2, 2023.