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cs.CL2023
Jointly Reparametrized Multi-Layer Adaptation for Efficient and Private Tuning
Umang Gupta, Aram Galstyan, Greg Ver Steeg
Efficient finetuning of pretrained language transformers is becoming increasingly prevalent for solving natural language processing tasks. While effective, it can still require a l…
cs.CL2023
Neural Architecture Search for Parameter-Efficient Fine-tuning of Large Pre-trained Language Models
Neal Lawton, Anoop Kumar, Govind Thattai +2
Parameter-efficient tuning (PET) methods fit pre-trained language models (PLMs) to downstream tasks by either computing a small compressed update for a subset of model parameters,…