LEVIATAN – Leveraging Open-source AI for Embedded Software Development

Simple item page
dc.contributor.authorAguet, Clémentine
dc.contributor.authorBerguerand, Robin
dc.contributor.authorBeysens, Jona
dc.contributor.authorHoover, David
dc.contributor.authorLahera Perez, Juan Alberto
dc.contributor.authorSafai-Naeeni, Reza
dc.contributor.authorRubio, Asun
dc.date.accessioned2025-11-11T15:37:48Z
dc.date.available2025-11-11T15:37:48Z
dc.date.issued2024
dc.description.abstractThis project aims to implement a large language model (LLM) agentic solution tailored for embedded code development. By utilizing open-source, self-hosted models, it ensures the use of confidential data without privacy concerns. Additionally, an automatic pipeline has been developed to facilitate the computation of metrics, assessing the performance of the solution and enabling its benchmarking with other solutions on the market. Ultimately, this project improves embedded software development engineers' productivity by focusing their effort on the most meaningful tasks.
dc.identifier.citationCSEM Scientific and Technical Report 2024, p. 14
dc.identifier.urihttps://hdl.handle.net/20.500.12839/1824
dc.titleLEVIATAN – Leveraging Open-source AI for Embedded Software Development
dc.typeCSEM Report
dc.type.csemdivisionsBU-D
dc.type.csemresearchareasDigital Health
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
2024_Aguet et al_LEVIATAN Leveraging Open-source AI for Embedded Software Development.pdf
Size:
461.69 KB
Format:
Adobe Portable Document Format
Download
Collections
Technical Marketing Material