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Self-Supervised Learning (SSL) has become a prominent paradigm for pre-training encoders to learning general-purpose representations from unlabeled data and releasing them on third-party platforms for broad downstream deep learning tasks.
Krizhevsky A, Hinton G, et al. (2009) Learning multiple layers of features from tiny images. Toronto, ON, Canada
2009
Earlier work this paper cites.
Coates A, Ng AY, Lee H (2011) An analysis of single-layer networks in unsupervised feature learning. In: Proceedings of the 14th International Conference on Artificial Intelligence and Statistics, JMLR.org, Fort Lauderdale, USA, vol 15, pp 215–223
2011
Earlier work this paper cites.
Netzer Y, Wang T, Coates A, Bissacco A, Wu B, Ng AY (2011) Reading digits in natural images with unsupervised feature learning
2011
Earlier work this paper cites.
Stallkamp J, Schlipsing M, Salmen J, Igel C (2012) Man vs. computer: Benchmarking machine learning algorithms for traffic sign recognition. Neural Networks 32(1):323–332
2012
Earlier work this paper cites.
Ba J, Caruana R (2014) Do deep nets really need to be deep? Advances in neural information processing systems 27
2014
Earlier work this paper cites.
Romero A, Ballas N, Kahou SE, Chassang A, Gatta C, Bengio Y (2014) Fitnets: Hints for thin deep nets. arXiv preprint arXiv:14126550
2014
Earlier work this paper cites.
Hinton G, Vinyals O, Dean J (2015) Distilling the knowledge in a neural network. arXiv preprint arXiv:150302531
2015
Earlier work this paper cites.
He K, Zhang X, Ren S, Sun J (2016) Deep residual learning for image recognition. In: Proceedings of the 26th conference on computer vision and pattern recognition, pp 770–778
2016
Earlier work this paper cites.
Zagoruyko S, Komodakis N (2016) Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer. OpenReview.net
2016
Earlier work this paper cites.
Liu Y, Ma S, Aafer Y, Lee WC, Zhai J, Wang W, Zhang X (2018b) Trojaning attack on neural networks. In: 25th Annual Network And Distributed System Security Symposium (NDSS 2018), Internet Soc
2018
Earlier work this paper cites.
Srinivas S, Fleuret F (2018) Knowledge transfer with jacobian matching. In: Proceedings of the 35th International Conference on Machine Learning, ICML 2018, Stockholmsmässan, Stockholm, Sweden, July 10-15, 2018, PMLR, pp 4723–4731
2018
Earlier work this paper cites.
Gu T, Liu K, Dolan-Gavitt B, Garg S (2019) Badnets: Evaluating backdooring attacks on deep neural networks. IEEE Access 7:47230–47244
2019
Earlier work this paper cites.
Lan Z, Chen M, Goodman S, Gimpel K, Sharma P, Soricut R (2019) Albert: A lite bert for self-supervised learning of language representations. arXiv preprint arXiv:190911942
2019
Earlier work this paper cites.
Peng B, Jin X, Liu J, Li D, Wu Y, Liu Y, Zhou S, Zhang Z (2019) Correlation congruence for knowledge distillation. In: Proceedings of the 29th International Conference on Computer Vision, pp 5007–5016
2019
Earlier work this paper cites.
Tung F, Mori G (2019) Similarity-preserving knowledge distillation. In: 2019 IEEE/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), October 27 - November 2, 2019, pp 1365–1374
2019
Earlier work this paper cites.
Baevski A, Zhou Y, Mohamed A, Auli M (2020) wav2vec 2.0: A framework for self-supervised learning of speech representations. Advances in neural information processing systems 33:12449–12460
2020
Earlier work this paper cites.
Chen T, Kornblith S, Norouzi M, Hinton G (2020a) A simple framework for contrastive learning of visual representations. In: Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, PMLR, pp 1597–1607
2020
Earlier work this paper cites.
Grill JB, Strub F, Altché F, Tallec C, Richemond P, Buchatskaya E, Doersch C, Avila Pires B, Guo Z, Gheshlaghi Azar M, et al. (2020) Bootstrap your own latent-a new approach to self-supervised learning. Advances in neural information processing systems 33:21271–21284
2020
Cited alongside, same era.
Jaiswal A, Babu AR, Zadeh MZ, Banerjee D, Makedon F (2020) A survey on contrastive self-supervised learning. Technologies 9(1):2
2020
Cited alongside, same era.
Khosla P, Teterwak P, Wang C, Sarna A, Tian Y, Isola P, Maschinot A, Liu C, Krishnan D (2020) Supervised contrastive learning. Advances in neural information processing systems 33:18661–18673
2020
Cited alongside, same era.
Liu Y, Ma X, Bailey J, Lu F (2020) Reflection backdoor: A natural backdoor attack on deep neural networks. In: Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part X 16, Springer, pp 182–199
2020
Cited alongside, same era.
He K, Chen X, Xie S, Li Y, Dollár P, Girshick RB (2022) Masked autoencoders are scalable vision learners. In: Proceedings of the 35th conference on computer vision and pattern recognition, IEEE, pp 15979–15988
2022
Later among the works it cites.
Saha A, Tejankar A, Koohpayegani SA, Pirsiavash H (2022) Backdoor attacks on self-supervised learning. In: Proceedings of the 32nd Conference on Computer Vision and Pattern Recognition, pp 13337–13346
2022
Later among the works it cites.
Tao G, Liu Y, Shen G, Xu Q, An S, Zhang Z, Zhang X (2022) Model orthogonalization: Class distance hardening in neural networks for better security. In: 43rd IEEE Symposium on Security and Privacy (SP), IEEE
2022
Later among the works it cites.
Wang Y, Braham NAA, Xiong Z, Liu C, Albrecht CM, Zhu XX (2022) Ssl4eo-s12: A large-scale multi-modal, multi-temporal dataset for self-supervised learning in earth observation. arXiv preprint arXiv:221107044
2022
Later among the works it cites.
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Saha A, Subramanya A, Pirsiavash H (2020) Hidden trigger backdoor attacks. In: Proceedings of the 34th AAAI conference on artificial intelligence, pp 11957–11965
2020
Cited alongside, same era.
Wang K, Gao X, Zhao Y, Li X, Dou D, Xu CZ (2019) Pay attention to features, transfer learn faster cnns. In: 8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020
2020
Cited alongside, same era.
Xu K, Rui L, Li Y, Gu L (2020) Feature normalized knowledge distillation for image classification. In: Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part XXV, Springer, pp 664–680
2020
Cited alongside, same era.
Zhao S, Ma X, Zheng X, Bailey J, Chen J, Jiang YG (2020) Clean-label backdoor attacks on video recognition models. In: Proceedings of the 30th conference on computer vision and pattern recognition, pp 14443–14452
2020
Cited alongside, same era.
Carlini N, Terzis A (2021) Poisoning and backdooring contrastive learning. arXiv preprint arXiv:210609667
2021
Cited alongside, same era.
Caron M, Touvron H, Misra I, Jégou H, Mairal J, Bojanowski P, Joulin A (2021) Emerging properties in self-supervised vision transformers. In: Proceedings of the 24th international conference on computer vision, pp 9650–9660
2021
Cited alongside, same era.
Cheng S, Liu Y, Ma S, Zhang X (2021) Deep feature space trojan attack of neural networks by controlled detoxification. In: Proceedings of the AAAI Conference on Artificial Intelligence, pp 1148–1156
2021
Cited alongside, same era.
Gan L, Li J, Zhang T, Li X, Meng Y, Wu F, Yang Y, Guo S, Fan C (2021) Triggerless backdoor attack for nlp tasks with clean labels. arXiv preprint arXiv:211107970
2021
Cited alongside, same era.
Balestriero R, Ibrahim M, Sobal V, Morcos A, Shekhar S, Goldstein T, Bordes F, Bardes A, Mialon G, Tian Y, et al. (2023) A cookbook of self-supervised learning. arXiv preprint arXiv:230412210
2023
Later among the works it cites.
Feng S, Tao G, Cheng S, Shen G, Xu X, Liu Y, Zhang K, Ma S, Zhang X (2023) Detecting backdoors in pre-trained encoders. In: Proceedings of the 33rd Conference on Computer Vision and Pattern Recognition (CVPR)
2023
Later among the works it cites.
Gou J, Yu B, Maybank SJ, Tao D (2023) Knowledge distillation: A survey. ACM Computing Surveys 55(6):1–37
2023
Later among the works it cites.
Li C, Pang R, Xi Z, Du T, Ji S, Yao Y, Wang T (2023) An embarrassingly simple backdoor attack on self-supervised learning. In: Proceedings of the IEEE/CVF International Conference on Computer Vision, pp 4367–4378
2023
Later among the works it cites.
Zhao S, Wen J, Tuan LA, Zhao J, Fu J (2023) Prompt as triggers for backdoor attack: Examining the vulnerability in language models. arXiv preprint arXiv:230501219
2023
Later among the works it cites.
Sun W, Zhang X, Lu H, Chen YC, Wang T, Chen J, Lin L (2024) Backdoor contrastive learning via bi-level trigger optimization. In: Proceedings of the 12th International Conference on Learning Representations
2024
Closest in time.
Xin C, Lu Y, Lin H, Zhou S, Zhu H, Wang W, Liu Z, Han X, Sun L (2024) Beyond full fine-tuning: Harnessing the power of lora for multi-task instruction tuning. In: Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), ELRA and ICCL, pp 2307–2317
2024
Closest in time.
Han T, Sun W, Ding Z, Fang C, Qian H, Li J, Chen Z, Zhang X (2025) Mutual information guided backdoor mitigation for pre-trained encoders. IEEE Transactions on Information Forensics and Security
2025
Closest in time.
Nguyen QH, Nguyen NN, Ta T, Nguyen‐Tang T, Wong K, Hoang TT, Doan KD (2025) Wicked oddities: Selectively poisoning for effective clean‐label backdoor attacks. In: International Conference on Learning Representations (ICLR) 2025
2025
Closest in time.
Ning L, Lara H, Guo M, Rastogi A (2025) Mode: Effective multi-task parameter efficient fine-tuning with a mixture of dyadic experts. In: Findings of the Association for Computational Linguistics: NAACL 2025, Association for Computational Linguistics, pp 8233–8246
2025
Closest in time.
Tao G, Wang Z, Feng S, Shen G, Ma S, Zhang X (2024) Distribution preserving backdoor attack in self‐supervised learning. In: 2024 IEEE Symposium on Security and Privacy, IEEE, pp 2029–2047
2047
Closest in time.
Jia J, Liu Y, Gong NZ (2022) Badencoder: Backdoor attacks to pre-trained encoders in self-supervised learning. In: Proceedings of the 43rd IEEE Symposium on Security and Privacy, IEEE, San Francisco, CA, USA, pp 2043–2059
2059
Closest in time.