1 citations · 4 across the 4 of their papers we have counts for
4 papers · 1 filter
Scoping Review of Active Learning Strategies and their Evaluation Environments for Entity Recognition Tasks
Philipp Kohl, Yoka Krämer, Claudia Fohry +1
We conducted a scoping review for active learning in the domain of natural language processing (NLP), which we summarize in accordance with the PRISMA-ScR guidelines as follows: Ob…
German Text Simplification: Finetuning Large Language Models with Semi-Synthetic Data
Lars Klöser, Mika Beele, Jan-Niklas Schagen +1
This study pioneers the use of synthetically generated data for training generative models in document-level text simplification of German texts. We demonstrate the effectiveness o…
Explaining Relation Classification Models with Semantic Extents
Lars Klöser, Andre Büsgen, Philipp Kohl +2
In recent years, the development of large pretrained language models, such as BERT and GPT, significantly improved information extraction systems on various tasks, including relati…
ALE: A Simulation-Based Active Learning Evaluation Framework for the Parameter-Driven Comparison of Query Strategies for NLP
Philipp Kohl, Nils Freyer, Yoka Krämer +5
Supervised machine learning and deep learning require a large amount of labeled data, which data scientists obtain in a manual, and time-consuming annotation process. To mitigate t…