2025
AdaMSS: Adaptive Multi-Subspace Approach for Parameter-Efficient Fine-Tuning
Extensive experiments across image classification, natural language understanding, and natural language generation tasks show that AdaMSS achieves comparable performance to full fine-tuning and outperforms other parameter-efficient fine-tuning methods in most cases, all while requiring fewer trainable parameters.
Jingjing Zheng, Wang-Long Lu, Yiming Dong et al.
· Neural Information Processin... · 0 citations