3 papers
cs.LG2026
DoRAN: Stabilizing Weight-Decomposed Low-Rank Adaptation via Noise Injection and Auxiliary Networks
Nghiem T. Diep, Hien Dang, Tuan Truong +3
Parameter-efficient fine-tuning (PEFT) methods have become the standard paradigm for adapting large-scale models. Among these techniques, Weight-Decomposed Low-Rank Adaptation (DoR…
cs.LG2026
A Statistical Theory of Gated Attention through the Lens of Hierarchical Mixture of Experts
Viet Nguyen, Tuan Minh Pham, Thinh Cao +4
Self-attention has greatly contributed to the success of the widely used Transformer architecture by enabling learning from data with long-range dependencies. In an effort to impro…
cs.LG2026
Hypernetwork-Driven Low-Rank Adaptation Across Attention Heads
Nghiem T. Diep, Dung Le, Tuan Truong +3
Parameter-efficient fine-tuning (PEFT) has emerged as a powerful paradigm for adapting large-scale pre-trained models to downstream tasks with minimal additional parameters. Among…