AutoLang: Anpassning av LLM för programvaruutveckling inom fordonsindustrin
Forskningsprojekt, 2024 – 2026

The primary objective of AutoLang is to adapt generalist, open-source LLMs to the automotive domain to help assist/automate language-based tasks in automotive engineering. Many task artifacts and work products of automotive engineering are natural language documents. The corollary, of course, is that automotive engineers spend significant effort creating/reviewing these
documents, or even taking actions based upon compiled documents. An AutoLang family of LLMs adapted to documents from automotive domains has the potential to assist/automate document-based engineering, significantly improving productivity.

Looking ahead, it's conceivable to apply this approach to other domains such as telecommunications or healthcare, with much of the underlying logic remaining applicable. This project sets a strong foundation for future research into domain-specific large language models.

Deltagare

Yinan Yu (kontakt)

Chalmers, Data- och informationsteknik, Funktionell programmering

Dhasarathy Parthasarathy

Chalmers, Data- och informationsteknik, Funktionell programmering

Samarbetspartners

Volvo Group

Gothenburg, Sweden

Finansiering

Chalmers AI-forskningscentrum (CHAIR)

Finansierar Chalmers deltagande under 2024–2026

Relaterade styrkeområden och infrastruktur

Informations- och kommunikationsteknik

Styrkeområden

Transport

Styrkeområden

Mer information

Senast uppdaterat

2024-09-27