Achievements
mdx1 > Pubulications > Achievements

We publish research outcomes obtained using mdx in this page.
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Awards

Press Releases

  • ARIM-mdx Data System: A New Data Platform Revolutionizing Materials Research with 900+ Active Users in Japan

    Article: https://www.t.u-tokyo.ac.jp/en/press/pr2024-12-13-001
    Papars:
    Conference: 2024 IEEE International Conference on Big Data (IEEE BigData 2024)
    Title: ARIM-mdx Data System: Towards a Nationwide Data Platform for Materials Science

    Authors: Masatoshi Hanai, Ryo Ishikawa, Mitsuaki Kawamura, Masato Ohnishi, Norio Takenaka, Kou Nakamura, Daiju Matsumura, Seiji Fujikawa, Hiroki Sakamoto, Yukinori Ochiai, Tetsuo Okane, Shin-Ichiro Kuroki, Atsuo Yamada, Toyotaro Suzumura, Junichiro Shiomi, Kenjiro Taura, Yoshio Mita, Naoya Shibata, Yuichi Ikuhara

Papers

  • Yoshiki Ogawa, Takuya Oki, Chenbo Zhao, Yoshihide Sekimoto, Chihiro Shimizu, Evaluating the subjective perceptions of streetscapes using street-view images, Landscape and Urban Planning, Volume 247, 2024, 105073, ISSN 0169-2046, https://doi.org/10.1016/j.landurbplan.2024.105073.
  • Chenbo Zhao, Yoshiki Ogawa, Shenglong Chen, Takuya Oki, Yoshihide Sekimoto, Quantitative land price analysis via computer vision from street view images, Engineering Applications of Artificial Intelligence, Volume 123, Part A, 2023, 106294, ISSN 0952-1976, https://doi.org/10.1016/j.engappai.2023.106294
  • Mingkang Chen, Jingtao Sun, Kento Aida, Atsuko Takefusa, Weather-aware object detection method for maritime surveillance systems, Future Generation Computer Systems, Volume 151, 2024, Pages 111-123, ISSN 0167-739X, https://doi.org/10.1016/j.future.2023.09.030
  • A. Kumar, T. Islam, J. Ma, T. Kashiyama, Y. Sekimoto and C. Mattmann, “WindSR: Improving Spatial Resolution of Satellite Wind Speed Through Super-Resolution,” in IEEE Access, vol. 11, pp. 69486-69494, 2023, https://doi.org/10.1109/ACCESS.2023.3292966
  • Y. Ogawa, C. Zhao, T. Oki, S. Chen and Y. Sekimoto, “Deep Learning Approach for Classifying the Built Year and Structure of Individual Buildings by Automatically Linking Street View Images and GIS Building Data,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 16, pp. 1740-1755, 2023, https://doi.org/10.1109/JSTARS.2023.3237509
  • Zhao C, Ogawa Y, Chen S, Oki T, Sekimoto Y. People Flow Trend Estimation Approach and Quantitative Explanation Based on the Scene Level Deep Learning of Street View Images. Remote Sensing. 2023; 15(5):1362. https://doi.org/10.3390/rs15051362
  • Nagasaki, M., Sekiya, Y., Asakura, A. et al. Design and implementation of a hybrid cloud system for large-scale human genomic research. Hum Genome Var 10, 6 (2023). https://doi.org/10.1038/s41439-023-00231-2
  • Shenglong Chen, Yoshiki Ogawa, Chenbo Zhao, Yoshihide Sekimoto, Large-scale individual building extraction from open-source satellite imagery via super-resolution-based instance segmentation approach, ISPRS Journal of Photogrammetry and Remote Sensing, Volume 195, 2023, Pages 129-152, ISSN 0924-2716, https://doi.org/10.1016/j.isprsjprs.2022.11.006

Preprints

  • Hanai, M., Ishikawa, R., Kawamura, M., Ohnishi, M., Takenaka, N., Nakamura, K., Matsumura, D., Fujikawa, S., Sakamoto, H., Ochiai, Y., Okane, T., Kuroki, S., Yamada, A., Suzumura, T., Shiomi, J., Taura, K., Mita, Y., Shibata, N., & Ikuhara, Y. (2024). ARIM-mdx Data System: Towards a Nationwide Data Platform for Materials Science. ArXiv, abs/2409.06734, https://doi.org/10.48550/arXiv.2409.06734
  • Aizawa, Akiko, et al. “LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs.” arXiv preprint arXiv:2407.03963 (2024).
  • Yanaka, Hitomi, Namgi Han, Ryoma Kumon, Jie Lu, Masashi Takeshita, Ryo Sekizawa, Taisei Kato and Hiromi Arai. “Analyzing Social Biases in Japanese Large Language Models.” (2024). https://api.semanticscholar.org/CorpusID:270226200
  • Ishikawa, Takuto, et al. “Sub-photon accuracy noise reduction of single shot coherent diffraction pattern with atomic model trained autoencoder.” arXiv preprint arXiv:2403.11992 (2024). https://doi.org/10.48550/arXiv.2403.11992
  • Gao, F., Jiang, H., Blum, M., Lu, J., Jiang, Y., & Li, I. (2023). Large Language Models on Wikipedia-Style Survey Generation: an Evaluation in NLP Concepts. ArXiv, abs/2308.10410. https://doi.org/10.48550/arXiv.2308.10410
  • Li, Z., Yang, B. (2023). NNKGC: Improving Knowledge Graph Completion with Node Neighborhoods. ArXiv, abs/2302.06132. https://doi.org/10.48550/arXiv.2302.06132
  • Kashiyama, T., Pang, Y., Sekimoto, Y., & Yabe, T. (2022). Pseudo-PFLOW: Development of nationwide synthetic open dataset for people movement based on limited travel survey and open statistical data. ArXiv, abs/2205.00657. https://doi.org/10.48550/arXiv.2205.00657

Proceedings

  • Junfeng Jiang, Fei Cheng, and Akiko Aizawa. 2024. Improving Referring Ability for Biomedical Language Models. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 6444–6457, Miami, Florida, USA. Association for Computational Linguistics. https://aclanthology.org/2024.findings-emnlp.375/
  • Masatoshi Hanai, Mitsuaki Kawamura, Ryo Ishikawa, Toyotaro Suzumura, and Kenjiro Taura. 2024. Cloud Data Acquisition from Shared-Use Facilities in A University-Scale Laboratory Information Management System. In Proceedings of the IEEE/ACM 16th International Conference on Utility and Cloud Computing (UCC ’23). Association for Computing Machinery, New York, NY, USA, Article 21, 1–9. https://doi.org/10.1145/3603166.3632147
  • K. Yasuoka, “Sequence-Labeling RoBERTa Model for Dependency-Parsing in Classical Chinese and Its Application to Vietnamese and Thai,” 2023 8th International Conference on Business and Industrial Research (ICBIR), Bangkok, Thailand, 2023, pp. 169-173, doi: 10.1109/ICBIR57571.2023.10147628.
  • Linxin Song, Yan Cui, Ao Luo, Freddy Lecue and Irene Li; Better Explain Transformers by Illuminating Important Information, EACL 2023, https://doi.org/10.48550/arXiv.2401.09972
  • C. Zhao, Y. Ogawa, S. Chen, Z. Yang and Y. Sekimoto, “Label Freedom: Stable Diffusion for Remote Sensing Image Semantic Segmentation Data Generation,” 2023 IEEE International Conference on Big Data (BigData), Sorrento, Italy, 2023, pp. 1022-1030, https://ieeexplore.ieee.org/document/10386381.
  • Linxin Song, Jieyu Zhang, Lechao Cheng, Pengyuan Zhou, Tianyi Zhou and Irene Li; NLPBench: Evaluating Large Language Models on Solving NLP Problems, Instruction Workshop @ NeurIPS, 2023,  https://doi.org/10.48550/arXiv.2309.15630
  • Ryuichiro Hataya, Han Bao, Hiromi Arai; Will Large-scale Generative Models Corrupt Future Datasets?; Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2023, pp. 20555-20565. https://openaccess.thecvf.com/content/ICCV2023/html/Hataya_Will_Large-scale_Generative_Models_Corrupt_Future_Datasets_ICCV_2023_paper.html
  • Nobuhiro Ueda, Kazumasa Omura, Takashi Kodama, Hirokazu Kiyomaru, Yugo Murawaki, Daisuke Kawahara, and Sadao Kurohashi. 2023. KWJA: A Unified Japanese Analyzer Based on Foundation Models. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 538–548, Toronto, Canada. Association for Computational Linguistics. http://dx.doi.org/10.18653/v1/2023.acl-demo.52
  • D. Huo et al., “Small Object Detection for Birds with Swin Transformer,” 2023 18th International Conference on Machine Vision and Applications (MVA), Hamamatsu, Japan, 2023, pp. 1-5, https://doi.org/10.23919/MVA57639.2023.10216093
  • Ryo Nakamura and Yohei Kuga. 2023. Multi-threaded scp: Easy and Fast File Transfer over SSH. In Practice and Experience in Advanced Research Computing (PEARC ’23). Association for Computing Machinery, New York, NY, USA, 320–323. https://doi.org/10.1145/3569951.3597582
  • R. Sasaki, A. Takefusa, H. Nakada and M. Oguchi, “Development and Evaluation of IoT System Consisting of ROS-based Robot, Edge and Cloud,” 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC), Torino, Italy, 2023, pp. 1737-1744, https://doi.org/10.1109/COMPSAC57700.2023.00268
  • A. Kumar, T. Kashiyama, H. Maeda, F. Zhang, H. Omata and Y. Sekimoto, “Vehicle re-identification and trajectory reconstruction using multiple moving cameras in the CARLA driving simulator,” 2022 IEEE International Conference on Big Data (Big Data), Osaka, Japan, 2022, pp. 1858-1865, https://doi.org/10.1109/BigData55660.2022.10020814
  • A. Kumar, T. Kashiyama, H. Maeda, H. Omata and Y. Sekimoto, “Citywide reconstruction of traffic flow using the vehicle-mounted moving camera in the CARLA driving simulator,” 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), Macau, China, 2022, pp. 2292-2299, https://doi.org/10.1109/ITSC55140.2022.9921927

Presentations

Invited Talk

      • Irene Li ,University of Tokyo, “A Journey from Transformers to Large Language Models: an Educational Perspective”, 2023 the 1st International Conference on AI-generated Content (AIGC2023), Aug. 2023

Poster Presentation

  • Zhenbo Wang, Akihito Taya, Takaaki Kato, Kaoru Sezaki, and Yuuki Nishiyama, “Toward Detecting Student-Athletes’ Condition Using Passive Mobile and Wearable Sensing”, UbiComp/ISWC 2024, Oct. 2024