SPIRA: Sparse Information-Geometric Rank Adaptation for Parameter-Efficient Fine-Tuning of Large Pretrained Models.
SPIRA is a PEFT framework that separates support discovery from parameter-efficient adaptation and remains competitive with representative PEFT baselines while using lower trainable-parameter budgets than several compared weight-side/LoRA-family baselines.