3 papers
cs.CL2025
Knowledge-augmented Pre-trained Language Models for Biomedical Relation Extraction
Mario Sänger, Ulf Leser
Automatic relationship extraction (RE) from biomedical literature is critical for managing the vast amount of scientific knowledge produced each year. In recent years, utilizing pr…
cs.CL2024
HunFlair2 in a cross-corpus evaluation of biomedical named entity recognition and normalization tools
Mario Sänger, Samuele Garda, Xing David Wang +5
With the exponential growth of the life science literature, biomedical text mining (BTM) has become an essential technology for accelerating the extraction of insights from publica…
cs.CL2020
HunFlair: An Easy-to-Use Tool for State-of-the-Art Biomedical Named Entity Recognition
Leon Weber, Mario Sänger, Jannes Münchmeyer +3
Summary: Named Entity Recognition (NER) is an important step in biomedical information extraction pipelines. Tools for NER should be easy to use, cover multiple entity types, highl…