3 papers
cs.CL2025
Contrastive Learning Using Graph Embeddings for Domain Adaptation of Language Models in the Process Industry
Anastasia Zhukova, Jonas Lührs, Christian E. Lobmüller +1
Recent trends in NLP utilize knowledge graphs (KGs) to enhance pretrained language models by incorporating additional knowledge from the graph structures to learn domain-specific t…
cs.CL2025
Efficient Domain-adaptive Continual Pretraining for the Process Industry in the German Language
Anastasia Zhukova, Christian E. Matt, Bela Gipp
Domain-adaptive continual pretraining (DAPT) is a state-of-the-art technique that further trains a language model (LM) on its pretraining task, e.g., masked language modeling (MLM)…
cs.CL2024
Automated Collection of Evaluation Dataset for Semantic Search in Low-Resource Domain Language
Anastasia Zhukova, Christian E. Matt, Bela Gipp
Domain-specific languages that use a lot of specific terminology often fall into the category of low-resource languages. Collecting test datasets in a narrow domain is time-consumi…