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cs.LG2024
Sparse Orthogonal Parameters Tuning for Continual Learning
Kun-Peng Ning, Hai-Jian Ke, Yu-Yang Liu +3
Continual learning methods based on pre-trained models (PTM) have recently gained attention which adapt to successive downstream tasks without catastrophic forgetting. These method…
cs.LG2024
Is Parameter Collision Hindering Continual Learning in LLMs?
Shuo Yang, Kun-Peng Ning, Yu-Yang Liu +4
Large Language Models (LLMs) often suffer from catastrophic forgetting when learning multiple tasks sequentially, making continual learning (CL) essential for their dynamic deploym…
cs.LG2021
Learning Twofold Heterogeneous Multi-Task by Sharing Similar Convolution Kernel Pairs
Quan Feng, Songcan Chen
Heterogeneous multi-task learning (HMTL) is an important topic in multi-task learning (MTL). Most existing HMTL methods usually solve either scenario where all tasks reside in the…