German Language Model

Research on German language models focuses on adapting existing architectures like BERT and RoBERTa to the specific challenges of the German language, including its flexible word order and rich morphology. Current efforts concentrate on improving performance in specialized domains like finance and medicine through domain-specific pre-training and exploring the impact of diverse versus high-quality training data. These advancements are crucial for improving natural language processing applications in German, addressing biases in existing models, and enabling more accurate and nuanced analysis of German text across various fields.