2 papers
cs.CV2025
Beyond Random Augmentations: Pretraining with Hard Views
Fabio Ferreira, Ivo Rapant, Jörg K. H. Franke +1
Self-Supervised Learning (SSL) methods typically rely on random image augmentations, or views, to make models invariant to different transformations. We hypothesize that the effica…
cs.CL2024
Transfer Learning for Finetuning Large Language Models
Tobias Strangmann, Lennart Purucker, Jörg K. H. Franke +3
As the landscape of large language models expands, efficiently finetuning for specific tasks becomes increasingly crucial. At the same time, the landscape of parameter-efficient fi…