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cs.DC2026
AutoEncoder-Compressed Parallel Split Learning for Pre-trained Model Fine-Tuning
Bas Meuwissen, Vasileios Tsouvalas, Nirvana Meratnia
Distributed Fine-Tuning (DFT) of large-scale Foundation Models (FMs) on resource-constrained edge devices is limited by local compute constraints and communication overhead. Parall…
cs.DC2025
Fine-tuning Multimodal Transformers on Edge: A Parallel Split Learning Approach
Timo Fudala, Vasileios Tsouvalas, Nirvana Meratnia
Multimodal transformers integrate diverse data types like images, audio, and text, advancing tasks such as audio-visual understanding and image-text retrieval; yet their high param…