Activation-Efficient Fine-Tuning via Sequence-Compressed Low-Rank Subspaces.

arXiv:2604.22783v2 Announce Type: replace-cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) has become the standard approach for adapting large language models (LLMs). However, despite reducing trainable parameter counts, many PEFT methods remain memory-b