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Bridging the gap between low-rank and orthogonal adaptation via householder reflection adaptation
While following different technical routes, both low-rank and orthogonal adaptation
techniques can efficiently adapt large-scale pre-training models in specific tasks or domains …
techniques can efficiently adapt large-scale pre-training models in specific tasks or domains …
Efficient Learning With Sine-Activated Low-rank Matrices
Low-rank decomposition has emerged as a vital tool for enhancing parameter efficiency in
neural network architectures, gaining traction across diverse applications in machine …
neural network architectures, gaining traction across diverse applications in machine …