AI & ML interests
Applied & domain-specific information extraction // Learning in low-resource settings and over large contexts // Construction and analysis of IE datasets, linguistic annotation // Multilingual information extraction // Evaluation methodology research // Explainability
DFKI-NLP is a Natural Language Processing group of researchers, software engineers and students at the Berlin office of the German Research Center for Artificial Intelligence (DFKI) working on basic and applied research in areas covering, among others, information extraction, knowledge base population, dialogue, sentiment analysis, and summarization. We are particularly interested in core research on learning in low-resource settings, reasoning over larger contexts, and continual learning. We strive for a deeper understanding of human language and thinking, with the goal of developing novel methods for processing and generating human language text, speech, and knowledge. An important part of our work is the creation of corpora, the evaluation of NLP datasets and tasks, and the explainability of (neural) models.
Our group forms a part of DFKI’s Speech and Language Technology department led by Prof. Sebastian Möller, and closely collaborates with e.g. the Technische Universität Berlin, the University of Potsdam's Computational Linguistics groups, DFKI’s Multilinguality and Language Technology department and TU Berlin’s Quality and Usability Group.
You can find Large Language Models published by (members of) our group here: LLMs by DFKI.