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Continual learning empowers models to adapt autonomously to the ever-changing environment or data streams without forgetting old knowledge.
Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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Learning multiple layers of features from tiny images
Alex Krizhevsky, Geoffrey Hinton, et al · 2009
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3d object representations for fine-grained categorization
Jonathan Krause, Michael Stark, Jia Deng, and Li Fei-Fei · 2013
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Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al · 2017
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Overcoming catastrophic forgetting by incremental moment matching
Sang-Woo Lee, Jin-Hwa Kim, Jaehyun Jun, Jung-Woo Ha, and Byoung-Tak Zhang · 2017
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Learning without forgetting
Zhizhong Li and Derek Hoiem · 2017
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icarl: Incremental classifier and representation learning
Sylvestre-Alvise Rebuffi, Alexander Kolesnikov, Georg Sperl, and Christoph H Lampert · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Memory aware synapses: Learning what (not) to forget
Rahaf Aljundi, Francesca Babiloni, Mohamed Elhoseiny, Marcus Rohrbach, and Tinne Tuytelaars · 2018
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Learn to grow: A continual structure learning framework for overcoming catastrophic forgetting
Xilai Li, Yingbo Zhou, Tianfu Wu, Richard Socher, and Caiming Xiong · 2019
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Moment matching for multi-source domain adaptation
Xingchao Peng, Qinxun Bai, Xide Xia, Zijun Huang, Kate Saenko, and Bo Wang · 2019
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Three scenarios for continual learning
Gido M Van de Ven and Andreas S Tolias · 2019
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Large scale incremental learning
Yue Wu, Yinpeng Chen, Lijuan Wang, Yuancheng Ye, Zicheng Liu, Yandong Guo, and Yun Fu · 2019
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Dark experience for general continual learning: a strong, simple baseline
Pietro Buzzega, Matteo Boschini, Angelo Porrello, Davide Abati, and Simone Calderara · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Continual learning of a mixed sequence of similar and dissimilar tasks
Zixuan Ke, Bing Liu, and Xingchang Huang · 2020
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A comprehensive study of class incremental learning algorithms for visual tasks
Eden Belouadah, Adrian Popescu, and Ioannis Kanellos · 2021
Cited alongside, same era.
A continual learning survey: Defying forgetting in classification tasks
Matthias De Lange, Rahaf Aljundi, Marc Masana, Sarah Parisot, Xu Jia, Aleš Leonardis, Gregory Slabaugh, and Tinne Tuytelaars · 2021
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Replay in deep learning: Current approaches and missing biological elements
Tyler L Hayes, Giri P Krishnan, Maxim Bazhenov, Hava T Siegelmann, Terrence J Sejnowski, and Christopher Kanan · 2021
Cited alongside, same era.
The many faces of robustness: A critical analysis of out-of-distribution generalization
Dan Hendrycks, Steven Basart, Norman Mu, Saurav Kadavath, Frank Wang, Evan Dorundo, Rahul Desai, Tyler Zhu, Samyak Parajuli, Mike Guo, et al · 2021
Cited alongside, same era.
Progressive voronoi diagram subdivision enables accurate data-free class-incremental learning
Chunwei Ma, Zhanghexuan Ji, Ziyun Huang, Yan Shen, Mingchen Gao, and Jinhui Xu · 2022
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Class-incremental learning: survey and performance evaluation on image classification
Marc Masana, Xialei Liu, Bartłomiej Twardowski, Mikel Menta, Andrew D Bagdanov, and Joost Van De Weijer · 2022
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An introduction to lifelong supervised learning
Shagun Sodhani, Mojtaba Faramarzi, Sanket Vaibhav Mehta, Pranshu Malviya, Mohamed Abdelsalam, Janarthanan Janarthanan, and Sarath Chandar · 2022
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Dynamic residual classifier for class incremental learning
Xiuwei Chen and Xiaobin Chang · 2023
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Birt: Bio-inspired replay in vision transformers for continual learning
Kishaan Jeeveswaran, Prashant Bhat, Bahram Zonooz, and Elahe Arani · 2023
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Brian Lester, Rami Al-Rfou, and Noah Constant · 2021
Cited alongside, same era.
An empirical investigation of the role of pre-training in lifelong learning
Sanket Vaibhav Mehta, Darshan Patil, Sarath Chandar, and Emma Strubell · 2021
Cited alongside, same era.
Effect of scale on catastrophic forgetting in neural networks
Vinay Venkatesh Ramasesh, Aitor Lewkowycz, and Ethan Dyer · 2021
Cited alongside, same era.
Always be dreaming: A new approach for data-free class-incremental learning
James Smith, Yen-Chang Hsu, Jonathan Balloch, Yilin Shen, Hongxia Jin, and Zsolt Kira · 2021
Cited alongside, same era.
Der: Dynamically expandable representation for class incremental learning
Shipeng Yan, Jiangwei Xie, and Xuming He · 2021
Cited alongside, same era.
Online coreset selection for rehearsal-based continual learning
Jaehong Yoon, Divyam Madaan, Eunho Yang, and Sung Ju Hwang · 2021
Cited alongside, same era.
On the effectiveness of lipschitz-driven rehearsal in continual learning
Lorenzo Bonicelli, Matteo Boschini, Angelo Porrello, Concetto Spampinato, and Simone Calderara · 2022
Cited alongside, same era.
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Introducing language guidance in prompt-based continual learning
Muhammad Gul Zain Ali Khan, Muhammad Ferjad Naeem, Luc Van Gool, Didier Stricker, Federico Tombari, and Muhammad Zeshan Afzal · 2023
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Pcr: Proxy-based contrastive replay for online class-incremental continual learning
Huiwei Lin, Baoquan Zhang, Shanshan Feng, Xutao Li, and Yunming Ye · 2023
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Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig · 2023
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Online class incremental learning on stochastic blurry task boundary via mask and visual prompt tuning
Jun-Yeong Moon, Keon-Hee Park, Jung Uk Kim, and Gyeong-Moon Park · 2023
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Space-time prompting for video class-incremental learning
Yixuan Pei, Zhiwu Qing, Shiwei Zhang, Xiang Wang, Yingya Zhang, Deli Zhao, and Xueming Qian · 2023
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Progressive prompts: Continual learning for language models
Anastasia Razdaibiedina, Yuning Mao, Rui Hou, Madian Khabsa, Mike Lewis, and Amjad Almahairi · 2023
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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
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When prompt-based incremental learning does not meet strong pretraining
Yu-Ming Tang, Yi-Xing Peng, and Wei-Shi Zheng · 2023
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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
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Hierarchical decomposition of prompt-based continual learning: Rethinking obscured sub-optimality
Liyuan Wang, Jingyi Xie, Xingxing Zhang, Mingyi Huang, Hang Su, and Jun Zhu · 2024
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