1 citations · 2 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 1 cited
Dynamic Layer Tying for Parameter-Efficient Transformers
Tamir David Hay, Lior Wolf
In the pursuit of reducing the number of trainable parameters in deep transformer networks, we employ Reinforcement Learning to dynamically select layers during training and tie th…
cs.CL2024★ 1 cited
PRILoRA: Pruned and Rank-Increasing Low-Rank Adaptation
Nadav Benedek, Lior Wolf
With the proliferation of large pre-trained language models (PLMs), fine-tuning all model parameters becomes increasingly inefficient, particularly when dealing with numerous downs…