1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.LG2024
Choice of PEFT Technique in Continual Learning: Prompt Tuning is Not All You Need
Martin Wistuba, Prabhu Teja Sivaprasad, Lukas Balles +1
Recent Continual Learning (CL) methods have combined pretrained Transformers with prompt tuning, a parameter-efficient fine-tuning (PEFT) technique. We argue that the choice of pro…
cs.CV2023★ 1 cited
PAUMER: Patch Pausing Transformer for Semantic Segmentation
Evann Courdier, Prabhu Teja Sivaprasad, François Fleuret
We study the problem of improving the efficiency of segmentation transformers by using disparate amounts of computation for different parts of the image. Our method, PAUMER, accomp…