Achievements
mdx1 > Pubulications > Achievements

We publish research outcomes obtained using mdx I in this page.
We verify citation information for mdx paper [https://doi.org/10.1109/DASC/PiCom/CBDCom/Cy55231.2022.9927975] on platforms like Google Scholar and Semantic Scholar.
If it is evident from the content that the research is based on mdx, we include it in this page without requiring you to register it personally.
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Thank you for your understanding and collaboration.

Awards

  • Runner-Up Solution Award (2nd)
    Small Object Detection for Birds with Swin Transformer
    Da Huo, Marc A. Kastner, Tingwei Liu, Yasutomo Kawanishi, Takatsugu Hirayama, Takahiro Komamizu, Ichiro Ide
    DOI: 10.23919/MVA57639.2023.10216093
    18th International Conference on Machine Vision Applications
  • Best Full Paper Runner-Up and the Best Student Paper Awards
    Going Beyond Local: Global Graph-Enhanced Personalized News Recommendations
    Boming Yang, Dairui Liu, Toyotaro Suzumura, Ruihai Dong and Irene Li
    https://dl.acm.org/doi/10.1145/3604915.3608801
    ACM RecSys ’23: Proceedings of the 17th ACM Conference on Recommender Systems, September 2023

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

  • C. Zhao, S. Chen, Y. Ogawa and Y. Sekimoto, “Reducing Annotation Effort: An Innovative Weakly Supervised System for Nationwide Building Extraction Leveraging Open-source Data,” in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, doi: 10.1109/JSTARS.2026.3697411.
  • Nakamura, K., Takenaka, N., Hanai, M. et al. Open electrolyte database generated via an automated molecular dynamics simulation framework. npj Comput Mater (2026). https://doi.org/10.1038/s41524-026-02093-y
  • Yi Ting Chung, Takaki Nakamura, Optimizing Object Storage Performance for Large File Uploading under Small-start Environments, Journal of Information Processing, 2026, 34 巻, p. 86-94, 公開日 2026/02/15, Online ISSN 1882-6652, https://doi.org/10.2197/ipsjjip.34.86
  • M. Ohmori, K. Ogawa, H. Kashiwazaki and T. Ikenaga, “Comparison of Congestion Controls for LEO Satellite Communications in the Wild,” 2026 IEEE 23rd Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA, 2026, pp. 1-6, doi: 10.1109/CCNC65079.2026.11366302.
  • Yokoyama, Hiroto & Umemoto, Takahiro & Kumada, Akiko & Sato, Masahiro. (2025). Extrapolative prediction of polymer properties using physics-informed hierarchical descriptors. Applied Physics Letters. 127. 10.1063/5.0292279. https://doi.org/10.1063/5.0292279
  • Shigeru TAKAHASHI, Fumi YOSHIDA, Hikaru KUBOTA, Hideo SAGAWA, and Takahiro IINO, “Revisiting the near-infrared color of Karin family asteroids”, Stars and Galaxies Vol. 8, https://www.jstage.jst.go.jp/article/starsandgalaxies/8/0/8_4/_pdf/-char/en
  • Koyama, Shihori and Oyama, Norihiro and Mizuno, Hideyuki and Ikeda, Atsushi. Enhanced collective vibrations in granular materials. Soft Matter, 2025,21, 3957-3964. http://dx.doi.org/10.1039/D5SM00141B
  • Lingfeng Liao, Yoshiki Ogawa, Chenbo Zhao, Yoshihide Sekimoto, ControlBldg: A variable-controlled generative framework for conditioned modeling of vast 3D urban buildings, ISPRS Journal of Photogrammetry and Remote Sensing, Volume 230, 2025, Pages 581-598, ISSN 0924-2716, https://doi.org/10.1016/j.isprsjprs.2025.09.026.
  • Chenbo Zhao, Yoshiki Ogawa, Shenglong Chen, Takuya Oki, Yoshihide Sekimoto, Street Space Quality Improvement: Fusion of Subjective Perception in Street View Image Generation, Information Fusion, Volume 125, 2026, 103467, ISSN 1566-2535, https://doi.org/10.1016/j.inffus.2025.103467.
  • C. Ito, A. Takefusa, H. Nakada and M. Oguchi, “A Study of Effective Compression Methods for IoT Communication,” 2025 IEEE International Conference on Consumer Electronics (ICCE), Las Vegas, NV, USA, 2025, pp. 1-6, doi: 10.1109/ICCE63647.2025.10929811.
  • Kozai, M., Tanaka, Y., Abe, S., Minamiyama, Y., Shinbori, A., & Kadokura, A. (2025). AMIDER: A Multidisciplinary Research Database and Its Application to Promote Open Science. Data Science Journal, 24, 7. https://doi.org/10.5334/dsj-2025-007
  • Jung, G., Alkemade, R.M., Bapst, V. et al. Roadmap on machine learning glassy dynamics. Nat Rev Phys (2025). https://doi.org/10.1038/s42254-024-00791-4
  • Takasuka, D., Satoh, M., Miyakawa, T., Kodama, C., Klocke, D., Stevens, B., Vidale, P. L., and Terai, C. R. (2024) A protocol and analysis of year-long simulations of global storm-resolving models and beyond. Progress in Earth and Planetary Science, 11, 66, https://doi.org/10.1186/s40645-024-00668-1
  • Ohta, R., Tanigawa, Y., Suzuki, Y. et al. A polygenic score method boosted by non-additive models. Nat Commun 15, 4433 (2024). https://doi.org/10.1038/s41467-024-48654-x
  • Caremel, Cedric and Kawahara, Yoshihiro and Nakajima, Kohei, “Hysteretic reservoir”, PhysRevApplied.22.064045, https://link.aps.org/doi/10.1103/PhysRevApplied.22.064045
  • Yoshitaka Matsuzaki, Tetsunori Inoue, Masaya Kubota, Hiroki Matsumoto, Tomoyuki Sato, Hikari Sakamoto, Daisuke Naito, Web application of an integrated simulation for aquatic environment assessment in coastal and estuarine areas, Environmental Modelling & Software, 2024, 106184, ISSN 1364-8152, https://doi.org/10.1016/j.envsoft.2024.106184.
  • Yokoyama, Hiroto & Shimakawa, Hajime & Kumada, Akiko & Sato, Masahiro. (2024). Modulating thermal and electrical conductivities in polymers: An approach toward extracting molecular design rules through atomistic simulations. Applied Physics Letters. 124. 10.1063/5.0198445. https://doi.org/10.1063/5.0198445
  • 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

  • Oyama, Norihiro, Yusuke Hara, Takeshi Kawasaki and Kang-Sahn Kim. “Zero-temperature Avalanche Criticality Governing Dynamical Heterogeneity in Supercooled Liquids.” (2026). https://doi.org/10.48550/arXiv.2604.03573
  • Oyama, Norihiro, Yusuke Hara, Takeshi Kawasaki and Kang-Sahn Kim. “Potential energy landscape picture of zero-temperature avalanche criticality governing dynamics in supercooled liquids.” (2026). https://doi.org/10.48550/arXiv.2604.03580
  • Kanazawa, Naoki, Yuto Morohoshi, Hitomi Takahashi, Yukio Kawashima, Hiroshi Horii and Kengo Nakajima. “Observability Architecture for Quantum-Centric Supercomputing Workflows.” (2025). https://doi.org/10.48550/arXiv.2512.05484
  • Haoran Hong, Zhuoneng Sui, Leo Uesaka, Hiromi Kudo, and Hill Hiroki Kobayashi. 2025. Exploring the Cockatoo’s Engagement with Audiovisual Stimuli: An Inclusive Avian-IoT Interaction Design. In Proceedings of the ACM 12th International Conference on Animal-Computer Interaction (ACI ’25). Association for Computing Machinery, New York, NY, USA, Article 12, 1–9. https://doi.org/10.1145/3768539.3768553
  • Naoshi Yamane, Michael Ryan Zielewski, Takaki Nakamura, and Takuo Suganuma. 2025. Chimera-VDB: Mixed-Precision Vector Database with HNSW Index for RAG-LLM. In Proceedings of the 16th ACM SIGOPS Asia-Pacific Workshop on Systems (APSys ’25). Association for Computing Machinery, New York, NY, USA, 61–67. https://doi.org/10.1145/3725783.3764411
  • T. Suzuki, Y. Matsumoto, S. -Y. Kim, J. -i. Kani and T. Yoshida, “Automated, Intent-Based, Scalable Software OLT Deployment by Container Orchestration and Generative AI,” 2025 30th OptoElectronics and Communications Conference (OECC) and 2025 International Conference on Photonics in Switching and Computing (PSC), Sapporo, Japan, 2025, pp. 1-4, doi: 10.23919/OECC/PSC62146.2025.11111548.
  • Harada, Yuto, Yusuke Yamauchi, Yusuke Oda, Yohei Oseki, Yusuke Miyao and Yu Takagi. “Massive Supervised Fine-tuning Experiments Reveal How Data, Layer, and Training Factors Shape LLM Alignment Quality.” (2025). https://doi.org/10.48550/arXiv.2506.14681
  • Inaba, T., Inui, K., Miyao, Y., Oseki, Y., Heinzerling, B., & Takagi, Y. (2025). How LLMs Learn: Tracing Internal Representations with Sparse Autoencoders. https://doi.org/10.48550/arXiv.2503.06394
  • 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

  • Suchun Xie, Hwichan Kim, Shota Sasaki, Kosuke Yamada, and Jun Suzuki. 2025. Can Language Neuron Intervention Reduce Non-Target Language Output?. In Proceedings of the 8th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP, pages 452–466, Suzhou, China. Association for Computational Linguistics. https://doi.org/10.18653/v1/2025.blackboxnlp-1.26
  • R. Sasaki, Y. Ishikawa, A. Takefusa and O. Masato, “Consideration of Attribute-Based Encryption Utilization in IoT Communication,” 2025 9th Cyber Security in Networking Conference (CSNet), Abu Dhabi, United Arab Emirates, 2025, pp. 1-8, doi: 10.1109/CSNet67572.2025.11288155.
  • Takahashi, S. et al. (2026). Development of AFCAL: An Asteroid Flux Density Calculator for ALMA Observations. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2025 Workshops. ICCSA 2025. Lecture Notes in Computer Science, vol 15890. Springer, Cham. https://doi.org/10.1007/978-3-031-97606-3_1
  • Yanaka, Hitomi, Xinqi He, Jie Lu, Namgi Han, Sunjin Oh, Ryoma Kumon, Yuma Matsuoka, Katsuhiko Watabe and Yuko Itatsu. “Intersectional Bias in Japanese Large Language Models from a Contextualized Perspective.” (2025). https://doi.org/10.48550/arXiv.2506.12327
  • M. Hanai et al., “ARIM-mdx Data System: Towards a Nationwide Data Platform for Materials Science,” 2024 IEEE International Conference on Big Data (BigData), Washington, DC, USA, 2024, pp. 2326-2333, doi: 10.1109/BigData62323.2024.10825674.
  • 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
  • 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, doi: 10.23919/MVA57639.2023.10216093.
  • 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

Oral Presentation

  • Kazuichi Oe, Tomoya Saito, Tomoya Tanjo, Jun Nishii, Koichi Okada, Keigo Yabuki, Takahiro Tamesue, You Wang, Atsuko Takefusa,”Toward Practical HPC Education with MCJ-CloudHub”, EduHPC-25: Workshop on Education for High Performance Computing, Nov. 2025
  • Suchun Xie, Shota Sasaki, Hwichan Kim, Yunmeng Li, Reina Akama and Jun Suzuki, “Understanding Cross-Lingual Generalization of English-Centric LLMs: The Role of Representation Similarity and Data Exposure”, PRICAI 2025: PACIFIC RIM INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE 2025, Nov. 2025

Poster Presentation

  • Masatoshi Hanai, “A Cloud-Enhanced Innovative Supercomputer System​ for the Integration of Simulation/Data/Learning/Inferencing”, ISC 2025, Jun. 2025
  • Hayakawa, Y.S., Ogura, T., Saito, H., Shimotoku, D., Kobayashi, H., “Developing 3D environmental data utilization platform in Human Geosciences: A preview”, Japan Geoscience Union Meeting 2025, May 2025
  • 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