Congfeng Cao

NeuroAda: Activating Each Neuron’s Potential for Parameter-Efficient Fine-Tuning

Existing parameter-efficient fine-tuning (PEFT) methods primarily fall into two categories: addition-based and selective in-situ adaptation. The former, such as LoRA, introduce additional modules to adapt the model to downstream tasks, offering strong memory efficiency. However, their representation