Natural Language Learning and Generation Lab

Prof. Dr. Steffen Eger

The Natural Language Learning & Generation (NLLG) group covers a broad range of topics in Natural Language Processing (NLP). Methodologically, we use machine learning and AI approaches – including the latest large language and foundation models – to tackle text related problems such as text classification, machine translation, summarization and their evaluation, also in interdisciplinary contexts with (digital) humanities researchers and social scientists. A special focus is thereby on generative AI approaches and their evaluation.        

Concurrently, the following topics are central to our research agenda: 

• evaluation methods and metrics for natural language generation (e.g. machine translation and summarization)
• multimodal text-to-image generation models in the scientific domain
• machine translation and text generation for literature and poetry 
• automatic generation and analysis of arguments (e.g., with constraints on emotionality and convincingness)
• social scientific analysis (e.g. solidarity with refugees and women) in diachronic and multilingual political corpora

Prof. Dr. Steffen Eger
Professor of Natural Language Learning and Generation