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To cope with real-world dynamics, an intelligent system needs to incrementally acquire, update, accumulate, and exploit knowledge throughout its lifetime.
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Catastrophic interference in connectionist networks: The sequential learning problem
Michael McCloskey and Neal J Cohen · 1989
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Robert A Jacobs, Michael I Jordan, Steven J Nowlan, and Geoffrey E Hinton · 1991
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Why there are complementary learning systems in the hippocampus and neocortex: insights from the successes and failures of connectionist models of learning and memory
James L McClelland, Bruce L McNaughton, and Randall C O’Reilly · 1995
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Metaplasticity: the plasticity of synaptic plasticity
Wickliffe C Abraham and Mark F Bear · 1996
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Autonomous agents as embodied ai
Stan Franklin · 1997
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What are the computations of the cerebellum, the basal ganglia and the cerebral cortex?
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Complementary roles of basal ganglia and cerebellum in learning and motor control
Kenji Doya · 2000
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Embodied artificial intelligence
Ron Chrisley · 2003
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The organization of recent and remote memories
Paul W Frankland and Bruno Bontempi · 2005
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Metaplasticity: tuning synapses and networks for plasticity
Wickliffe C Abraham · 2008
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Activity-dependent gating of lateral inhibition in the mouse olfactory bulb
Armen C Arevian, Vikrant Kapoor, and Nathaniel N Urban · 2008
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Ongoing in vivo experience triggers synaptic metaplasticity in the neocortex
Roger L Clem, Tansu Celikel, and Alison L Barth · 2008
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Hippocampal replay of extended experience
Thomas J Davidson, Fabian Kloosterman, and Matthew A Wilson · 2009
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The elements of statistical learning: data mining, inference, and prediction
Trevor Hastie, Robert Tibshirani, Jerome H Friedman, and Jerome H Friedman · 2009
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Stably maintained dendritic spines are associated with lifelong memories
Guang Yang, Feng Pan, and Wen-Biao Gan · 2009
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Hippocampal replay in the awake state: a potential substrate for memory consolidation and retrieval
Margaret F Carr, Shantanu P Jadhav, and Loren M Frank · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Determinantal point processes for machine learning
Alex Kulesza, Ben Taskar, et al · 2012
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Mushroom body output neurons encode valence and guide memory-based action selection in drosophila
Yoshinori Aso, Divya Sitaraman, Toshiharu Ichinose, Karla R Kaun, Katrin Vogt, Ghislain Belliart-Guérin, Pierre-Yves Plaçais, Alice A Robie, Nobuhiro Yamagata, Christopher Schnaitmann, et al · 2014
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A pac-bayesian bound for lifelong learning
Anastasia Pentina and Christoph Lampert · 2014
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Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Structural components of synaptic plasticity and memory consolidation
Craig H Bailey, Eric R Kandel, and Kristen M Harris · 2015
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Coordinated and compartmentalized neuromodulation shapes sensory processing in drosophila
Raphael Cohn, Ianessa Morantte, and Vanessa Ruta · 2015
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Fast r-cnn
Ross Girshick · 2015
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Labelling and optical erasure of synaptic memory traces in the motor cortex
Akiko Hayashi-Takagi, Sho Yagishita, Mayumi Nakamura, Fukutoshi Shirai, Yi I Wu, Amanda L Loshbaugh, Brian Kuhlman, Klaus M Hahn, and Haruo Kasai · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Optimizing neural networks with kronecker-factored approximate curvature
James Martens and Roger Grosse · 2015
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Dopaminergic neurons write and update memories with cell-type-specific rules
Yoshinori Aso and Gerald M Rubin · 2016
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Inability to activate rac1-dependent forgetting contributes to behavioral inflexibility in mutants of multiple autism-risk genes
Tao Dong, Jing He, Shiqing Wang, Lianzhang Wang, Yuqi Cheng, and Yi Zhong · 2016
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What learning systems do intelligent agents need? complementary learning systems theory updated
Dharshan Kumaran, Demis Hassabis, and James L McClelland · 2016
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Andrei A Rusu, Neil C Rabinowitz, Guillaume Desjardins, Hubert Soyer, James Kirkpatrick, Koray Kavukcuoglu, Razvan Pascanu, and Raia Hadsell · 2016
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Neural plasticity: Dopamine tunes the mushroom body output network
Scott Waddell · 2016
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Expert gate: Lifelong learning with a network of experts
Rahaf Aljundi, Punarjay Chakravarty, and Tinne Tuytelaars · 2017
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A closer look at memorization in deep networks
Devansh Arpit, Stanislaw Jastrzebski, Nicolas Ballas, David Krueger, Emmanuel Bengio, Maxinder S Kanwal, Tegan Maharaj, Asja Fischer, Aaron Courville, Yoshua Bengio, et al · 2017
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Active bias: Training more accurate neural networks by emphasizing high variance samples
Haw-Shiuan Chang, Erik Learned-Miller, and Andrew McCallum · 2017
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Pathnet: Evolution channels gradient descent in super neural networks
Chrisantha Fernando, Dylan Banarse, Charles Blundell, Yori Zwols, David Ha, Andrei A Rusu, Alexander Pritzel, and Daan Wierstra · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
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On quadratic penalties in elastic weight consolidation
Ferenc Huszár · 2017
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Origins of cell-type-specific olfactory processing in the drosophila mushroom body circuit
Kengo Inada, Yoshiko Tsuchimoto, and Hokto Kazama · 2017
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On large-batch training for deep learning: Generalization gap and sharp minima
Nitish Shirish Keskar, Jorge Nocedal, Ping Tak Peter Tang, Dheevatsa Mudigere, and Mikhail Smelyanskiy · 2017
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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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Focal loss for dense object detection
Tsung-Yi Lin, Priya Goyal, Ross Girshick, Kaiming He, and Piotr Dollár · 2017
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Core50: a new dataset and benchmark for continuous object recognition
Vincenzo Lomonaco and Davide Maltoni · 2017
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Gradient episodic memory for continual learning
David Lopez-Paz and Marc’Aurelio Ranzato · 2017
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Communication-efficient learning of deep networks from decentralized data
Brendan McMahan, Eider Moore, Daniel Ramage, Seth Hampson, and Blaise Aguera y Arcas · 2017
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Encoder based lifelong learning
Amal Rannen, Rahaf Aljundi, Matthew B Blaschko, and Tinne Tuytelaars · 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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The persistence and transience of memory
Blake A Richards and Paul W Frankland · 2017
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Continual learning in generative adversarial nets
Ari Seff, Alex Beatson, Daniel Suo, and Han Liu · 2017
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Continual learning with deep generative replay
Hanul Shin, Jung Kwon Lee, Jaehong Kim, and Jiwon Kim · 2017
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Incremental learning of object detectors without catastrophic forgetting
Konstantin Shmelkov, Cordelia Schmid, and Karteek Alahari · 2017
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A deep hierarchical approach to lifelong learning in minecraft
Chen Tessler, Shahar Givony, Tom Zahavy, Daniel Mankowitz, and Shie Mannor · 2017
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Neural discrete representation learning
Aaron Van Den Oord, Oriol Vinyals, et al · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Continual learning through synaptic intelligence
Friedemann Zenke, Ben Poole, and Surya Ganguli · 2017
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Life-long disentangled representation learning with cross-domain latent homologies
Alessandro Achille, Tom Eccles, Loic Matthey, Chris Burgess, Nicholas Watters, Alexander Lerchner, and Irina Higgins · 2018
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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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End-to-end incremental learning
Francisco M Castro, Manuel J Marín-Jiménez, Nicolás Guil, Cordelia Schmid, and Karteek Alahari · 2018
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Riemannian walk for incremental learning: Understanding forgetting and intransigence
Arslan Chaudhry, Puneet K Dokania, Thalaiyasingam Ajanthan, and Philip HS Torr · 2018
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Efficient lifelong learning with a-gem
Arslan Chaudhry, Marc’Aurelio Ranzato, Marcus Rohrbach, and Mohamed Elhoseiny · 2018
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Lifelong machine learning
Zhiyuan Chen and Bing Liu · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Parvalbumin+ interneurons obey unique connectivity rules and establish a powerful lateral-inhibition microcircuit in dentate gyrus
Claudia Espinoza, Segundo Jose Guzman, Xiaomin Zhang, and Peter Jonas · 2018
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Loss surfaces, mode connectivity, and fast ensembling of dnns
Timur Garipov, Pavel Izmailov, Dmitrii Podoprikhin, Dmitry P Vetrov, and Andrew G Wilson · 2018
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Exemplar-supported generative reproduction for class incremental learning
Chen He, Ruiping Wang, Shiguang Shan, and Xilin Chen · 2018
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Lifelong learning via progressive distillation and retrospection
Saihui Hou, Xinyu Pan, Chen Change Loy, Zilei Wang, and Dahua Lin · 2018
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Re-evaluating continual learning scenarios: A categorization and case for strong baselines
Yen-Chang Hsu, Yen-Cheng Liu, Anita Ramasamy, and Zsolt Kira · 2018
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Selective experience replay for lifelong learning
David Isele and Akansel Cosgun · 2018
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Averaging weights leads to wider optima and better generalization
Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry Vetrov, and Andrew Gordon Wilson · 2018
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Continual reinforcement learning with complex synapses
Christos Kaplanis, Murray Shanahan, and Claudia Clopath · 2018
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Fearnet: Brain-inspired model for incremental learning
Ronald Kemker and Christopher Kanan · 2018
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Rotate your networks: Better weight consolidation and less catastrophic forgetting
Xialei Liu, Marc Masana, Luis Herranz, Joost Van de Weijer, Antonio M Lopez, and Andrew D Bagdanov · 2018
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Piggyback: Adapting a single network to multiple tasks by learning to mask weights
Arun Mallya, Dillon Davis, and Svetlana Lazebnik · 2018
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Packnet: Adding multiple tasks to a single network by iterative pruning
Arun Mallya and Svetlana Lazebnik · 2018
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Variational continual learning
Cuong V Nguyen, Yingzhen Li, Thang D Bui, and Richard E Turner · 2018
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Film: Visual reasoning with a general conditioning layer
Ethan Perez, Florian Strub, Harm De Vries, Vincent Dumoulin, and Aaron Courville · 2018
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Learning to learn without forgetting by maximizing transfer and minimizing interference
Matthew Riemer, Ignacio Cases, Robert Ajemian, Miao Liu, Irina Rish, Yuhai Tu, and Gerald Tesauro · 2018
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Online structured laplace approximations for overcoming catastrophic forgetting
Hippolyt Ritter, Aleksandar Botev, and David Barber · 2018
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Towards a natural benchmark for continual learning
Jonathan Schwarz, Daniel Altman, Andrew Dudzik, Oriol Vinyals, Yee Whye Teh, and Razvan Pascanu · 2018
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Progress & compress: A scalable framework for continual learning
Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, and Raia Hadsell · 2018
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Overcoming catastrophic forgetting with hard attention to the task
Joan Serra, Didac Suris, Marius Miron, and Alexandros Karatzoglou · 2018
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Natural variational continual learning
Hanna Tseran, Mohammad Emtiyaz Khan, Tatsuya Harada, and Thang D Bui · 2018
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Memory replay gans: Learning to generate new categories without forgetting
Chenshen Wu, Luis Herranz, Xialei Liu, Joost van de Weijer, Bogdan Raducanu, et al · 2018
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Reinforced continual learning
Ju Xu and Zhanxing Zhu · 2018
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Lifelong learning with dynamically expandable networks
Jaehong Yoon, Eunho Yang, Jeongtae Lee, and Sung Ju Hwang · 2018
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Mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cisse, Yann N Dauphin, and David Lopez-Paz · 2018
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Active protection: Learning-activated raf/mapk activity protects labile memory from rac1-independent forgetting
Xuchen Zhang, Qian Li, Lianzhang Wang, Zhong-Jian Liu, and Yi Zhong · 2018
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Continual learning with adaptive weights (claw)
Tameem Adel, Han Zhao, and Richard E Turner · 2019
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Uncertainty-based continual learning with adaptive regularization
Hongjoon Ahn, Sungmin Cha, Donggyu Lee, and Taesup Moon · 2019
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Online continual learning with maximal interfered retrieval
Rahaf Aljundi, Eugene Belilovsky, Tinne Tuytelaars, Laurent Charlin, Massimo Caccia, Min Lin, and Lucas Page-Caccia · 2019
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Task-free continual learning
Rahaf Aljundi, Klaas Kelchtermans, and Tinne Tuytelaars · 2019
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Gradient based sample selection for online continual learning
Rahaf Aljundi, Min Lin, Baptiste Goujaud, and Yoshua Bengio · 2019
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Il2m: Class incremental learning with dual memory
Eden Belouadah and Adrian Popescu · 2019
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Re-evaluating circuit mechanisms underlying pattern separation
N Alex Cayco-Gajic and R Angus Silver · 2019
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On tiny episodic memories in continual learning
Arslan Chaudhry, Marcus Rohrbach, Mohamed Elhoseiny, Thalaiyasingam Ajanthan, Puneet K Dokania, Philip HS Torr, and Marc’Aurelio Ranzato · 2019
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Episodic memory in lifelong language learning
Cyprien de Masson D’Autume, Sebastian Ruder, Lingpeng Kong, and Dani Yogatama · 2019
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Learning without memorizing
Prithviraj Dhar, Rajat Vikram Singh, Kuan-Chuan Peng, Ziyan Wu, and Rama Chellappa · 2019
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Uncertainty-guided continual learning with bayesian neural networks
Sayna Ebrahimi, Mohamed Elhoseiny, Trevor Darrell, and Marcus Rohrbach · 2019
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Continual learning via neural pruning
Siavash Golkar, Michael Kagan, and Kyunghyun Cho · 2019
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Psycholinguistics meets continual learning: Measuring catastrophic forgetting in visual question answering
Claudio Greco, Barbara Plank, Raquel Fernández, and Raffaella Bernardi · 2019
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Visualizing and understanding the effectiveness of bert
Yaru Hao, Li Dong, Furu Wei, and Ke Xu · 2019
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An end-to-end architecture for class-incremental object detection with knowledge distillation
Yu Hao, Yanwei Fu, Yu-Gang Jiang, and Qi Tian · 2019
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Learning a unified classifier incrementally via rebalancing
Saihui Hou, Xinyu Pan, Chen Change Loy, Zilei Wang, and Dahua Lin · 2019
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Parameter-efficient transfer learning for nlp
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly · 2019
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Overcoming catastrophic forgetting for continual learning via model adaptation
Wenpeng Hu, Zhou Lin, Bing Liu, Chongyang Tao, Zhengwei Tao Tao, Dongyan Zhao, Jinwen Ma, and Rui Yan · 2019
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Compacting, picking and growing for unforgetting continual learning
Ching-Yi Hung, Cheng-Hao Tu, Cheng-En Wu, Chien-Hung Chen, Yi-Ming Chan, and Chu-Song Chen · 2019
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Meta-learning representations for continual learning
Khurram Javed and Martha White · 2019
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Reconciling meta-learning and continual learning with online mixtures of tasks
Ghassen Jerfel, Erin Grant, Tom Griffiths, and Katherine A Heller · 2019
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Policy consolidation for continual reinforcement learning
Christos Kaplanis, Murray Shanahan, and Claudia Clopath · 2019
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Continual learning with bayesian neural networks for non-stationary data
Richard Kurle, Botond Cseke, Alexej Klushyn, Patrick Van Der Smagt, and Stephan Günnemann · 2019
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Overcoming catastrophic forgetting with unlabeled data in the wild
Kibok Lee, Kimin Lee, Jinwoo Shin, and Honglak Lee · 2019
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A neural dirichlet process mixture model for task-free continual learning
Soochan Lee, Junsoo Ha, Dongsu Zhang, and Gunhee Kim · 2019
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Rilod: Near real-time incremental learning for object detection at the edge
Dawei Li, Serafettin Tasci, Shalini Ghosh, Jingwen Zhu, Junting Zhang, and Larry Heck · 2019
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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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Continual learning for sentence representations using conceptors
Tianlin Liu, Lyle Ungar, and Joao Sedoc · 2019
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Adaptive online planning for continual lifelong learning
Kevin Lu, Igor Mordatch, and Pieter Abbeel · 2019
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Incremental learning techniques for semantic segmentation
Umberto Michieli and Pietro Zanuttigh · 2019
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Learning to remember: A synaptic plasticity driven framework for continual learning
Oleksiy Ostapenko, Mihai Puscas, Tassilo Klein, Patrick Jahnichen, and Moin Nabi · 2019
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Dopamine and cognitive control in prefrontal cortex
Torben Ott and Andreas Nieder · 2019
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Continual lifelong learning with neural networks: A review
German I Parisi, Ronald Kemker, Jose L Part, Christopher Kanan, and Stefan Wermter · 2019
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Continual learning by asymmetric loss approximation with single-side overestimation
Dongmin Park, Seokil Hong, Bohyung Han, and Kyoung Mu Lee · 2019
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Random path selection for incremental learning
Jathushan Rajasegaran, Munawar Hayat, Salman Khan, Fahad Shahbaz Khan, and Ling Shao · 2019
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Continual unsupervised representation learning
Dushyant Rao, Francesco Visin, Andrei Rusu, Razvan Pascanu, Yee Whye Teh, and Raia Hadsell · 2019
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Scalable recollections for continual lifelong learning
Matthew Riemer, Tim Klinger, Djallel Bouneffouf, and Michele Franceschini · 2019
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Experience replay for continual learning
David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy Lillicrap, and Gregory Wayne · 2019
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Complementary learning for overcoming catastrophic forgetting using experience replay
Mohammad Rostami, Soheil Kolouri, and Praveen K Pilly · 2019
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A progressive model to enable continual learning for semantic slot filling
Yilin Shen, Xiangyu Zeng, and Hongxia Jin · 2019
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Lamol: Language modeling for lifelong language learning
Fan-Keng Sun, Cheng-Hao Ho, and Hung-Yi Lee · 2019
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Improving and understanding variational continual learning
Siddharth Swaroop, Cuong V Nguyen, Thang D Bui, and Richard E Turner · 2019
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Functional regularisation for continual learning with gaussian processes
Michalis K Titsias, Jonathan Schwarz, Alexander G de G Matthews, Razvan Pascanu, and Yee Whye Teh · 2019
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Three scenarios for continual learning
Gido M Van de Ven and Andreas S Tolias · 2019
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Continual learning with hypernetworks
Johannes von Oswald, Christian Henning, Benjamin F Grewe, and João Sacramento · 2019
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Incremental learning from scratch for task-oriented dialogue systems
Weikang Wang, Jiajun Zhang, Qian Li, Mei-Yuh Hwang, Chengqing Zong, and Zhifei Li · 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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Incremental learning using conditional adversarial networks
Ye Xiang, Ying Fu, Pan Ji, and Hua Huang · 2019
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Scalable and order-robust continual learning with additive parameter decomposition
Jaehong Yoon, Saehoon Kim, Eunho Yang, and Sung Ju Hwang · 2019
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Continual learning of context-dependent processing in neural networks
Guanxiong Zeng, Yang Chen, Bo Cui, and Shan Yu · 2019
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Lifelong gan: Continual learning for conditional image generation
Mengyao Zhai, Lei Chen, Frederick Tung, Jiawei He, Megha Nawhal, and Greg Mori · 2019
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Xingyi Zhou, Dequan Wang, and Philipp Krähenbühl · 2019
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Conditional channel gated networks for task-aware continual learning
Davide Abati, Jakub Tomczak, Tijmen Blankevoort, Simone Calderara, Rita Cucchiara, and Babak Ehteshami Bejnordi · 2020
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Eec: Learning to encode and regenerate images for continual learning
Ali Ayub and Alan Wagner · 2020
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Learning to continually learn
Shawn Beaulieu, Lapo Frati, Thomas Miconi, Joel Lehman, Kenneth O Stanley, Jeff Clune, and Nick Cheney · 2020
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Scail: Classifier weights scaling for class incremental learning
Eden Belouadah and Adrian Popescu · 2020
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Generalisation guarantees for continual learning with orthogonal gradient descent
Mehdi Abbana Bennani, Thang Doan, and Masashi Sugiyama · 2020
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Continual lifelong learning in natural language processing: A survey
Magdalena Biesialska, Katarzyna Biesialska, and Marta R Costa-jussà · 2020
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Coresets via bilevel optimization for continual learning and streaming
Zalán Borsos, Mojmir Mutny, and Andreas Krause · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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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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Online learned continual compression with adaptive quantization modules
Lucas Caccia, Eugene Belilovsky, Massimo Caccia, and Joelle Pineau · 2020
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Online fast adaptation and knowledge accumulation (osaka): a new approach to continual learning
Massimo Caccia, Pau Rodriguez, Oleksiy Ostapenko, Fabrice Normandin, Min Lin, Lucas Page-Caccia, Issam Hadj Laradji, Irina Rish, Alexandre Lacoste, David Vázquez, et al · 2020
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Modeling the background for incremental learning in semantic segmentation
Fabio Cermelli, Massimiliano Mancini, Samuel Rota Bulo, Elisa Ricci, and Barbara Caputo · 2020
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Cpr: Classifier-projection regularization for continual learning
Sungmin Cha, Hsiang Hsu, Taebaek Hwang, Flavio Calmon, and Taesup Moon · 2020
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Continual learning in low-rank orthogonal subspaces
Arslan Chaudhry, Naeemullah Khan, Puneet Dokania, and Philip Torr · 2020
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Mitigating forgetting in online continual learning via instance-aware parameterization
Hung-Jen Chen, An-Chieh Cheng, Da-Cheng Juan, Wei Wei, and Min Sun · 2020
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Online continual learning from imbalanced data
Aristotelis Chrysakis and Marie-Francine Moens · 2020
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Continual learning for affective robotics: Why, what and how?
Nikhil Churamani, Sinan Kalkan, and Hatice Gunes · 2020
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Routing networks with co-training for continual learning
Mark Collier, Efi Kokiopoulou, Andrea Gesmundo, and Jesse Berent · 2020
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Gan memory with no forgetting
Yulai Cong, Miaoyun Zhao, Jianqiao Li, Sijia Wang, and Lawrence Carin · 2020
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Ratt: Recurrent attention to transient tasks for continual image captioning
Riccardo Del Chiaro, Bartłomiej Twardowski, Andrew Bagdanov, and Joost Van de Weijer · 2020
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Podnet: Pooled outputs distillation for small-tasks incremental learning
Arthur Douillard, Matthieu Cord, Charles Ollion, Thomas Robert, and Eduardo Valle · 2020
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Adversarial continual learning
Sayna Ebrahimi, Franziska Meier, Roberto Calandra, Trevor Darrell, and Marcus Rohrbach · 2020
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Remembering for the right reasons: Explanations reduce catastrophic forgetting
Sayna Ebrahimi, Suzanne Petryk, Akash Gokul, William Gan, Joseph E Gonzalez, Marcus Rohrbach, et al · 2020
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The turking test: Can language models understand instructions?
Avia Efrat and Omer Levy · 2020
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Orthogonal gradient descent for continual learning
Mehrdad Farajtabar, Navid Azizan, Alex Mott, and Ang Li · 2020
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Online continual learning under extreme memory constraints
Enrico Fini, Stéphane Lathuiliere, Enver Sangineto, Moin Nabi, and Elisa Ricci · 2020
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Sharpness-aware minimization for efficiently improving generalization
Pierre Foret, Ariel Kleiner, Hossein Mobahi, and Behnam Neyshabur · 2020
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Eternal sunshine of the spotless net: Selective forgetting in deep networks
Aditya Golatkar, Alessandro Achille, and Stefano Soatto · 2020
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Investigating catastrophic forgetting during continual training for neural machine translation
Shuhao Gu and Yang Feng · 2020
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Look-ahead meta learning for continual learning
Gunshi Gupta, Karmesh Yadav, and Liam Paull · 2020
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Continual learning of a mixed sequence of similar and dissimilar tasks
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Meta-consolidation for continual learning
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Optimal continual learning has perfect memory and is np-hard
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Continual learning with extended kronecker-factored approximate curvature
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Residual continual learning
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Continual learning for robotics: Definition, framework, learning strategies, opportunities and challenges
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Class-incremental learning with strong pre-trained models
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General incremental learning with domain-aware categorical representations
Jiangwei Xie, Shipeng Yan, and Xuming He · 2022
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Geometry of sequence working memory in macaque prefrontal cortex
Yang Xie, Peiyao Hu, Junru Li, Jingwen Chen, Weibin Song, Xiao-Jing Wang, Tianming Yang, Stanislas Dehaene, Shiming Tang, Bin Min, et al · 2022
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Meta-attention for vit-backed continual learning
Mengqi Xue, Haofei Zhang, Jie Song, and Mingli Song · 2022
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Generative negative text replay for continual vision-language pretraining
Shipeng Yan, Lanqing Hong, Hang Xu, Jianhua Han, Tinne Tuytelaars, Zhenguo Li, and Xuming He · 2022
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Uncertainty-aware contrastive distillation for incremental semantic segmentation
Guanglei Yang, Enrico Fini, Dan Xu, Paolo Rota, Mingli Ding, Moin Nabi, Xavier Alameda-Pineda, and Elisa Ricci · 2022
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Task-free continual learning via online discrepancy distance learning
Fei Ye and Adrian G Bors · 2022
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Learning with recoverable forgetting
Jingwen Ye, Yifang Fu, Jie Song, Xingyi Yang, Songhua Liu, Xin Jin, Mingli Song, and Xinchao Wang · 2022
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Contintin: Continual learning from task instructions
Wenpeng Yin, Jia Li, and Caiming Xiong · 2022
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Continual learning by modeling intra-class variation
Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, and Weiyang Liu · 2022
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Self-training for class-incremental semantic segmentation
Lu Yu, Xialei Liu, and Joost Van de Weijer · 2022
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Representation compensation networks for continual semantic segmentation
Chang-Bin Zhang, Jia-Wen Xiao, Xialei Liu, Ying-Cong Chen, and Ming-Ming Cheng · 2022
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Cglb: Benchmark tasks for continual graph learning
Xikun Zhang, Dongjin Song, and Dacheng Tao · 2022
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Epicker is an exemplar-based continual learning approach for knowledge accumulation in cryoem particle picking
Xinyu Zhang, Tianfang Zhao, Jiansheng Chen, Yuan Shen, and Xueming Li · 2022
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A simple but strong baseline for online continual learning: Repeated augmented rehearsal
Yaqian Zhang, Bernhard Pfahringer, Eibe Frank, Albert Bifet, Nick Jin Sean Lim, and Yunzhe Jia · 2022
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Continual sequence generation with adaptive compositional modules
Yanzhe Zhang, Xuezhi Wang, and Diyi Yang · 2022
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Static-dynamic co-teaching for class-incremental 3d object detection
Na Zhao and Gim Hee Lee · 2022
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Forward compatible few-shot class-incremental learning
Da-Wei Zhou, Fu-Yun Wang, Han-Jia Ye, Liang Ma, Shiliang Pu, and De-Chuan Zhan · 2022
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Few-shot class-incremental learning by sampling multi-phase tasks
Da-Wei Zhou, Han-Jia Ye, Liang Ma, Di Xie, Shiliang Pu, and De-Chuan Zhan · 2022
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Self-sustaining representation expansion for non-exemplar class-incremental learning
Kai Zhu, Wei Zhai, Yang Cao, Jiebo Luo, and Zheng-Jun Zha · 2022
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Continual prompt tuning for dialog state tracking
Qi Zhu, Bing Li, Fei Mi, Xiaoyan Zhu, and Minlie Huang · 2022
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Margin-based few-shot class-incremental learning with class-level overfitting mitigation
Yixiong Zou, Shanghang Zhang, Yuhua Li, and Ruixuan Li · 2022
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Task-aware information routing from common representation space in lifelong learning
Prashant Shivaram Bhat, Bahram Zonooz, and Elahe Arani · 2023
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Towards label-efficient incremental learning: A survey
Mert Kilickaya, Joost Van der Weijer, and Yuki Asano · 2023
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Alexander Kirillov, Eric Mintun, Nikhila Ravi, Hanzi Mao, Chloe Rolland, Laura Gustafson, Tete Xiao, Spencer Whitehead, Alexander C Berg, Wan-Yen Lo, et al · 2023
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Yong Lin, Lu Tan, Hangyu Lin, Zeming Zheng, Renjie Pi, Jipeng Zhang, Shizhe Diao, Haoxiang Wang, Han Zhao, Yuan Yao, et al · 2023
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Overcoming recency bias of normalization statistics in continual learning: Balance and adaptation
Yilin Lyu, Liyuan Wang, Xingxing Zhang, Zicheng Sun, Hang Su, Jun Zhu, and Liping Jing · 2023
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Gpt-4 technical report
OpenAI · 2023
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First session adaptation: A strong replay-free baseline for class-incremental learning
Aristeidis Panos, Yuriko Kobe, Daniel Olmeda Reino, Rahaf Aljundi, and Richard E Turner · 2023
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The ideal continual learner: An agent that never forgets
Liangzu Peng, Paris Giampouras, and René Vidal · 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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Hierarchical decomposition of prompt-based continual learning: Rethinking obscured sub-optimality
Liyuan Wang, Jingyi Xie, Xingxing Zhang, Mingyi Huang, Hang Su, and Jun Zhu · 2023
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Incorporating neuro-inspired adaptability for continual learning in artificial intelligence
Liyuan Wang, Xingxing Zhang, Qian Li, Mingtian Zhang, Hang Su, Jun Zhu, and Yi Zhong · 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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Genetic dissection of mutual interference between two consecutive learning tasks in drosophila
Jianjian Zhao, Xuchen Zhang, Bohan Zhao, Wantong Hu, Tongxin Diao, Liyuan Wang, Yi Zhong, and Qian Li · 2023
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