PrefixMemory-Tuning: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention

arXiv:2506.13674v3 Announce Type: replace-cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) methods have become crucial for rapidly adapting large language models (LLMs) to downstream tasks. Prefix-Tuning, an early and effective PEFT technique, demonstrated the ability to achieve performance comparable to full fine-tuning with significantly reduced computational and memory overhead. However, despite its earlier success, its effectiveness in training modern state-of-the-art LLMs has been ver