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We introduce \textbf{Knowledge Swapping}, a novel task designed to selectively regulate knowledge of a pretrained model by enabling the forgetting of user\-specified information, retaining essential knowledge, and acquiring new knowledge simultaneously.
Model selection and estimation in regression with grouped variables
Yuan, M. and Lin, Y · 2006
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Pascal voc 2008 challenge
Hoiem, D., Divvala, S. K., and Hays, J. H · 2009
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Novel datasets for fine-grained image categorization
Dataset, E · 2011
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The caltech-ucsd birds-200-2011 dataset
Wah, C., Branson, S., Welinder, P., Perona, P., and Belongie, S · 2011
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Cats and dogs
Parkhi, O. M., Vedaldi, A., Zisserman, A., and Jawahar, C · 2012
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Microsoft coco: Common objects in context
Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Dollár, P., and Zitnick, C. L · 2014
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Sparse convolutional neural networks
Liu, B., Wang, M., Foroosh, H., Tappen, M., and Pensky, M · 2015
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Rusu, A. A., Rabinowitz, N. C., Desjardins, G., Soyer, H., Kirkpatrick, J., Kavukcuoglu, K., Pascanu, R., and Hadsell, R · 2016
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Learning structured sparsity in deep neural networks
Wen, W., Wu, C., Wang, Y., Chen, Y., and Li, H · 2016
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Remote sensing image scene classification: Benchmark and state of the art
Cheng, G., Han, J., and Lu, X · 2017
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Overcoming catastrophic forgetting in neural networks
Kirkpatrick, J., Pascanu, R., Rabinowitz, N., Veness, J., Desjardins, G., Rusu, A. A., Milan, K., Quan, J., Ramalho, T., Grabska-Barwinska, A., et al · 2017
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Understanding black-box predictions via influence functions
Koh, P. W. and Liang, P · 2017
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Learning without forgetting
Li, Z. and Hoiem, D · 2017
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icarl: Incremental classifier and representation learning
Rebuffi, S.-A., Kolesnikov, A., Sperl, G., and Lampert, C. H · 2017
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Deepglobe 2018: A challenge to parse the earth through satellite images
Demir, I., Koperski, K., Lindenbaum, D., Pang, G., Huang, J., Basu, S., Hughes, F., Tuia, D., and Raskar, R · 2018
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Identification of plant leaf diseases using a nine-layer deep convolutional neural network
Geetharamani, G. and Pandian, A · 2019
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Does learning require memorization? a short tale about a long tail
Feldman, V · 2020
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Transformer feed-forward layers are key-value memories
Geva, M., Schuster, R., Berant, J., and Levy, O · 2020
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Dino: Detr with improved denoising anchor boxes for end-to-end object detection
Zhang, H., Li, F., Liu, S., Zhang, L., Su, H., Zhu, J., Ni, L. M., and Shum, H.-Y · 2022
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A model or 603 exemplars: Towards memory-efficient class-incremental learning
Zhou, D.-W., Wang, Q.-W., Ye, H.-J., and Zhan, D.-C · 2022
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Pcr: Proxy-based contrastive replay for online class-incremental continual learning
Lin, H., Zhang, B., Feng, S., Li, X., and Ye, Y · 2023
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Decoupling learning and remembering: A bilevel memory framework with knowledge projection for task-incremental learning
Sun, W., Li, Q., Zhang, J., Wang, W., and Geng, Y.-a · 2023
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Task difficulty aware parameter allocation & regularization for lifelong learning
Wang, W., Hu, Y., Chen, Q., and Zhang, Y · 2023
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Per-pixel classification is not all you need for semantic segmentation
Cheng, B., Schwing, A., and Kirillov, A · 2021
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Pre-trained models: Past, present and future
Han, X., Zhang, Z., Ding, N., Gu, Y., Liu, X., Huo, Y., Qiu, J., Yao, Y., Zhang, A., Zhang, L., et al · 2021
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Lora: Low-rank adaptation of large language models
Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., and Chen, W · 2021
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Prototype augmentation and self-supervision for incremental learning
Zhu, F., Zhang, X.-Y., Wang, C., Yin, F., and Liu, C.-L · 2021
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Class-incremental learning with cross-space clustering and controlled transfer
Ashok, A., Joseph, K., and Balasubramanian, V. N · 2022
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Dytox: Transformers for continual learning with dynamic token expansion
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Continual semantic segmentation with automatic memory sample selection
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Llm-assisted multi-teacher continual learning for visual question answering in robotic surgery
Chen, K., Du, Y., You, T., Islam, M., Guo, Z., Jin, Y., Chen, G., and Heng, P.-A · 2024
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Towards unbounded machine unlearning
Kurmanji, M., Triantafillou, P., Hayes, J., and Triantafillou, E · 2024
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Atlas: Adapter-based multi-modal continual learning with a two-stage learning strategy
Li, H., Tan, Z., Li, X., and Huang, W · 2024
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Revisiting neural networks for continual learning: An architectural perspective
Lu, A., Feng, T., Yuan, H., Song, X., and Sun, Y · 2024
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A comprehensive survey of continual learning: theory, method and application
Wang, L., Zhang, X., Su, H., and Zhu, J · 2024
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Defensive unlearning with adversarial training for robust concept erasure in diffusion models
Zhang, Y., Chen, X., Jia, J., Zhang, Y., Fan, C., Liu, J., Hong, M., Ding, K., and Liu, S · 2024
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Towards efficient and effective unlearning of large language models for recommendation
Wang, H., Lin, J., Chen, B., Yang, Y., Tang, R., Zhang, W., and Yu, Y · 2025
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