Machine intelligence and natural language processing

Research on generative AI, LLMs, federated learning, RAG, and AI-powered automation.

Artificial intelligence and language processing are key factors for automation, efficiency gains, and innovation in businesses and society. Despite major advances in recent years, significant challenges remain in terms of scalability, domain adaptation, explainability, and the responsible use of AI systems. Our research area develops advanced methods in machine intelligence and natural language processing to support companies in analysis, automation, and decision-making.

The focus is on the development and application of large language models, retrieval-augmented generation, and domain-specific AI solutions that can handle complex language and knowledge processing tasks and be flexibly adapted to different application areas. We support companies in integrating AI-based assistance systems, implementing federated learning, and developing methods for unlearning to ensure data protection, adaptability, and regulatory compliance. Close collaboration with industry partners results in innovative solutions that increase efficiency, enable new business models, and strengthen competitiveness in the long term. Our research places particular emphasis on the explainability and transparency of AI systems in order to gain user trust and increase acceptance in practice.

We develop practical tools and frameworks that help companies use AI responsibly and profitably. Empirical studies and pilot projects demonstrate a significant improvement in precision, adaptability, and efficiency in real-world applications. Our work helps to fully exploit the potential of AI and language processing and prepare companies for the challenges and opportunities of the digital future.

Latest publications

Jahr
Year
Titel/Autor:in
Title/Author
Publikationstyp
Publication Type
2025 Supporting Software Engineers in IT Security and Privacy through Automated Knowledge Discovery
Ehl, Marco; Ahmadian, Amir Shayan; Großer, Katharina; Elsofi, Duaa Adel Ali; Herrmann, Marc; Specht, Alexander; Schneider, Kurt; Jürjens, Jan
Konferenzbeitrag
Conference Paper
2025 Innamark: A Whitespace Replacement Information-Hiding Method
Hellmeier, Malte; Norkowski, Hendrik; Schrewe, Ernst-Christoph; Qarawlus, Haydar Khalid Haydar; Howar, Falk
Zeitschriftenaufsatz
Journal Article
2025 Evaluation of a large language model to simplify discharge summaries and provide cardiological lifestyle recommendations
Rust, Paul; Frings, Julian; Meister, Sven; Fehring, Leonard
Zeitschriftenaufsatz
Journal Article
2025 With Great Power Comes Great Responsibility: Responsible Management of Artificial Intelligence in Supporting Design Research Activities
Schoormann, Thorsten; Gupta, Samrat; Möller, Frederik; Chandra-Kruse, Leona
Konferenzbeitrag
Conference Paper
2024 Safe AI in Autonomous Vehicles. Track at AISoLA 2023
Howar, Falk; Hungar, Hardi
Konferenzbeitrag
Conference Paper
2024 Challenges and Opportunities for Enabling the Next Generation of Cross-Domain Dataspaces
Deshmukh, Rohit; Collarana Vargas, Diego; Gelhaar, Joshua; Theissen-Lipp, Johannes; Lange-Bever, Christoph; Arnold, Benedikt Tobias; Curry, Edward; Decker, Stefan
Konferenzbeitrag
Conference Paper
Diese Liste ist ein Auszug aus der Publikationsplattform Fraunhofer-Publica

This list has been generated from the publication platform Fraunhofer-Publica