3 papers
cs.LG2025
Survey of Active Learning Hyperparameters: Insights from a Large-Scale Experimental Grid
Julius Gonsior, Tim Rieß, Anja Reusch +3
Annotating data is a time-consuming and costly task, but it is inherently required for supervised machine learning. Active Learning (AL) is an established method that minimizes hum…
cs.CL2025
MAMUT: A Novel Framework for Modifying Mathematical Formulas for the Generation of Specialized Datasets for Language Model Training
Jonathan Drechsel, Anja Reusch, Steffen Herbold
Mathematical formulas are a fundamental and widely used component in various scientific fields, serving as a universal language for expressing complex concepts and relationships. W…
cs.LG2022
To Softmax, or not to Softmax: that is the question when applying Active Learning for Transformer Models
Julius Gonsior, Christian Falkenberg, Silvio Magino +3
Despite achieving state-of-the-art results in nearly all Natural Language Processing applications, fine-tuning Transformer-based language models still requires a significant amount…