3 papers
cs.CL2025
Exploring Gender Bias in Large Language Models: An In-depth Dive into the German Language
Kristin Gnadt, David Thulke, Simone Kopeinik +1
In recent years, various methods have been proposed to evaluate gender bias in large language models (LLMs). A key challenge lies in the transferability of bias measurement methods…
cs.CL2025
Listen to the Context: Towards Faithful Large Language Models for Retrieval Augmented Generation on Climate Questions
David Thulke, Jakob Kemmler, Christian Dugast +1
Large language models that use retrieval augmented generation have the potential to unlock valuable knowledge for researchers, policymakers, and the public by making long and techn…
eess.AS2025
Medical Spoken Named Entity Recognition
Khai Le-Duc, David Thulke, Hung-Phong Tran +4
Spoken Named Entity Recognition (NER) aims to extract named entities from speech and categorise them into types like person, location, organization, etc. In this work, we present V…