mdx: A Cloud Platform for Supporting Data Science and Cross-Disciplinary Research Collaborations
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Abstract (arXiv)
The growing amount of data and advances in data science have created a need for a new kind of cloud platform that provides users with flexibility, strong security, and the ability to couple with supercomputers and edge devices through high-performance networks. We have built such a nation-wide cloud platform, called "mdx" to meet this need. The mdx platform's virtualization service, jointly operated by 9 national universities and 2 national research institutes in Japan, launched in 2021, and more features are in development. Currently mdx is used by researchers in a wide variety of domains, including materials informatics, geo-spatial information science, life science, astronomical science, economics, social science, and computer science. This paper provides an the overview of the mdx platform, details the motivation for its development, reports its current status, and outlines its future plans.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). Builds on 0 of its 29 references that are in the map. First posted on arXiv 27 Mar 2022.
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Citing papers per year: 2024: 3; 2025: 3; 2026: 2.
8 papers.
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- 2025Intersectional Bias in Japanese Large Language Models from a Contextualized Perspectivecited by 0
- 2025Small Object Detection for Birds with Swin Transformercited by 0
- 2026Synth-JDoc: Synthesizing a Japanese Document Image Dataset for OCR with Diverse Layouts and Embedded Imagescited by 0
- 2026Synthetic Pre-pretraining Survives Scale, but Not as a Grammatical Priorcited by 0
- 2026Synthetic Pre-pretraining Survives Scale, but Not as a Grammatical Prior30 Sep 2026
- 2026Synth-JDoc: Synthesizing a Japanese Document Image Dataset for OCR with Diverse Layouts and Embedded Images28 Aug 2026
- 2025Small Object Detection for Birds with Swin Transformer27 Nov 2025
- 2025Massive Supervised Fine-tuning Experiments Reveal How Data, Layer, and Training Factors Shape LLM Alignment Quality17 Jun 2025
- 2025Intersectional Bias in Japanese Large Language Models from a Contextualized Perspective14 Jun 2025
- 2024Graph Adapter of EEG Foundation Models for Parameter Efficient Fine Tuning25 Nov 2024
- 2024LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs4 Jul 2024
- 2024JBBQ: Japanese Bias Benchmark for Analyzing Social Biases in Large Language Models4 Jun 2024