Efficient language models for SMEs (More-With-Less)
Large language models are insufficiently adapted to the needs of German SMEs. The goal of the project is to develop methods and a framework for the efficient adaptation of language models for SME-specific applications. In the BHT subproject, data- and model-centric approaches will be explored and prototypically tested for three use cases: (1) automated text authoring for the finance industry, (2) document matching for legal tech companies, and (3) improved reading order recognition in legal and finance documents.
Partners:
- Merantix Labs GmbH 2txt NLG GmbH
- Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. (IAIS)
Associated Partners:
- Aleph Alpha
- Börsenmedien AG
- briink GmbH
- caralegal GmbH
- finanztreff GmbH
- hessian.AI
- KI Bundesverband
- K.I.E.Z
- L-One Systems GmbH
Funded by:
BMBF - KI in Unternehmen
