PILOT: A Pre-Trained Model-Based Continual Learning Toolbox

Learning to prompt for continual learning

Zifeng Wang, Zizhao Zhang, Chen-Yu Lee, Han Zhang, Ruoxi Sun, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, and Tomas Pfister · 2022

Earlier work this paper cites.

Dualprompt: Complementary prompting for rehearsal-free continual learning

Zifeng Wang, Zizhao Zhang, Sayna Ebrahimi, Ruoxi Sun, Han Zhang, Chen-Yu Lee, Xiaoqi Ren, Guolong Su, Vincent Perot, Jennifer Dy, et al · 2022

Earlier work this paper cites.

Coda-prompt: Continual decomposed attention-based prompting for rehearsal-free continual learning

James Seale Smith, Leonid Karlinsky, Vyshnavi Gutta, Paola Cascante-Bonilla, Donghyun Kim, Assaf Arbelle, Rameswar Panda, Rogerio Feris, and Zsolt Kira · 2023

Earlier work this paper cites.

Slca: Slow learner with classifier alignment for continual learning on a pre-trained model

Gengwei Zhang, Liyuan Wang, Guoliang Kang, Ling Chen, and Yunchao Wei · 2023

Cited alongside, same era.

A unified continual learning framework with general parameter-efficient tuning

Qiankun Gao, Chen Zhao, Yifan Sun, Teng Xi, Gang Zhang, Bernard Ghanem, and Jian Zhang · 2023

Cited alongside, same era.

Continual learning with pre-trained models: A survey

Da-Wei Zhou, Hai-Long Sun, Jingyi Ning, Han-Jia Ye, and De-Chuan Zhan · 2024

Cited alongside, same era.

Revisiting class-incremental learning with pre-trained models: Generalizability and adaptivity are all you need

Da-Wei Zhou, Zi-Wen Cai, Han-Jia Ye, De-Chuan Zhan, and Ziwei Liu · 2024

Closest in time.

Ranpac: Random projections and pre-trained models for continual learning

Mark D McDonnell, Dong Gong, Amin Parvaneh, Ehsan Abbasnejad, and Anton van den Hengel · 2024

Closest in time.

Expandable subspace ensemble for pre-trained model-based class-incremental learning

Da-Wei Zhou, Hai-Long Sun, Han-Jia Ye, and De-Chuan Zhan · 2024

Closest in time.