2026
SALR: Sparsity-Aware Low-Rank Representation for Efficient Fine-Tuning of Large Language Models
AAAI 2026technical
Adapting large pre-trained language models to downstream tasks often entails fine-tuning millions of parameters or deploying costly dense weight updates, which hinders their use in resource-constrained environments. Low-rank Adaptation (LoRA) reduces trainable parameters by factorizing weight update