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cs.LG2024
Robust and Efficient Fine-tuning of LLMs with Bayesian Reparameterization of Low-Rank Adaptation
Ayan Sengupta, Vaibhav Seth, Arinjay Pathak +5
Large Language Models (LLMs) are highly resource-intensive to fine-tune due to their enormous size. While low-rank adaptation is a prominent parameter-efficient fine-tuning approac…
cs.CL2024
Step-by-Step Unmasking for Parameter-Efficient Fine-tuning of Large Language Models
Aradhye Agarwal, Suhas K Ramesh, Ayan Sengupta +1
Fine-tuning large language models (LLMs) on downstream tasks requires substantial computational resources. Selective PEFT, a class of parameter-efficient fine-tuning (PEFT) methodo…