Large language models (LLMs) have proven the ability to assist diverse users in conducting a variety of individual tasks via intuitive and natural conversations. This thesis discusses a utilization of LLMs as a tool for informed decision-making in energy investments and operations. One major goal is to transform the way the consumers engage with home ...
As universities strive to enhance the effectiveness of their lecture exercises, there arises a need for diverse and realistic test user scenarios to evaluate the understandability and usefulness of educational materials. However, in creating such scenarios a number of challenges arise: Real world students can rarely be used for testing, they are likely inexperienced or ...
Fine-tuning pre-trained large language models (LLMs) enhances biomedical text mining. This thesis introduces a tool capable of performing tasks such as Named Entity Recognition (NER), Normalization (NEN), and Knowledge Graph Construction (KGC). A key research question explores how LLMs can address the challenges of named entity recognition, normalization, and relation extraction in biomedical contexts.
This thesis aims to explore the realm of Natural Language Processing (NLP) in the context of automated grading systems, focusing specifically on identifying and analyzing frequent learner mistakes. With the increasing integration of technology in education, automated grading systems have gained prominence, but they often lack nuanced understanding and feedback provision. This research endeavors to ...
Large language models (LLMs) have proven the ability to assist diverse users in conducting a variety of individual tasks via intuitive and natural conversations. This thesis discusses a utilization of LLMs to perform (semi-)automated data processing and analyses on time series data. One major goal is to reduce expertise-related dependencies, allowing more people to manipulate ...
Validating the Reference Architecture Model of International Data Spaces Regarding Vocabulary Sharing Requirements From Life-Science Industry in the Context of Persistent Identifier Systems
