arxiv
PublishedOctober 19, 2026 at 4:00 AM
Activation-Efficient Fine-Tuning via Sequence-Compressed Low-Rank Subspaces
Publisher summary· verbatim
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-bound by token-level activation intermedi
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Originally published on arxiv ↗