This repository contains the official implementation for our ICML 2025 paper: Exploiting Presentative Feature Distributions for Parameter-Efficient Continual Learning of Large Language Models.
Generate the training script by executing:
python gen_script_new_{benchmark}_{model}.py
Then run the resulting script to start the training.
Compute key metrics including: Average Performance (AP), Forgetting Rate (F.Ra), Forward Transfer (FWT) and Backward Transfer (BWT). Execute the following command:
python score.py your_result_path single_result_path
The code of this repository partly relies on SAPT and we would like to show our sincere gratitude to authors of it.