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cs.LG2024
: towards data-free Transferable Parameter Efficient Finetuning
Runqian Wang, Soumya Ghosh, David Cox +4
Low-rank adapters (LoRA) and their variants are popular parameter-efficient fine-tuning (PEFT) techniques that closely match full model fine-tune performance while requiring only a…
cs.LG2024
Adaptive Memory Replay for Continual Learning
James Seale Smith, Lazar Valkov, Shaunak Halbe +4
Foundation Models (FMs) have become the hallmark of modern AI, however, these models are trained on massive data, leading to financially expensive training. Updating FMs as new dat…