Language Technologies

The Language Technologies Department conducts interdisciplinary research at the intersection of machine learning, natural language processing, and data science. It combines two research groups – the Data Science & Language Technologies Group as well as the Applied Machine Learning Lab. The department collaborates closely with the Bonn-Aachen International Center for Information Technology (b-it) and the Lamarr Institute for Machine Learning and Artificial Intelligence.

Its research focuses on application-driven, interpretable, and resource-efficient learning systems. Topics include representation learning for textual data, personalized information systems, and robust, fair, and efficient AI technologies. Applications span medical informatics, financial and legal document analysis, and behavioral analytics.

In addition, the department advances methods that make large language models (LLMs) more robust to data issues, allowing for more efficient and reliable learning with less effort, particularly for underrepresented user groups. Other core areas include the incorporation of factual knowledge, advanced reasoning, and common sense to mitigate hallucination; enabling advanced personalization and perspective-taking for safer and more empathetic interactions; and analyzing and improving the alignment of LLMs with human moral and ethical values.

The department is committed to addressing socially relevant challenges through transparent and innovative technology, contributing to the advancement of language and data processing systems.