30 citations · 95 across the 9 of their papers we have counts for
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cs.CL2023★ 30 cited
Multitask Prompt Tuning Enables Parameter-Efficient Transfer Learning
Zhen Wang, Rameswar Panda, Leonid Karlinsky +3
Prompt tuning, in which a base pretrained model is adapted to each task via conditioning on learned prompt vectors, has emerged as a promising approach for efficiently adapting lar…
cs.LG2023★ 13 cited
Learning to Grow Pretrained Models for Efficient Transformer Training
Peihao Wang, Rameswar Panda, Lucas Torroba Hennigen +6
Scaling transformers has led to significant breakthroughs in many domains, leading to a paradigm in which larger versions of existing models are trained and released on a periodic…