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Text-to-image diffusion models have achieved remarkable success in generating photorealistic images.
The right to be forgotten
Rosen, J. 2011 · 2011
Earlier work this paper cites.
Domain-adversarial training of neural networks
Ganin, Y.; Ustinova, E.; Ajakan, H.; Germain, P.; Larochelle, H.; Laviolette, F.; March, M.; and Lempitsky, V. 2016 · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M.; Ramsauer, H.; Unterthiner, T.; Nessler, B.; and Hochreiter, S. 2017 · 2017
Earlier work this paper cites.
Membership inference attacks against machine learning models
Shokri, R.; Stronati, M.; Song, C.; and Shmatikov, V. 2017 · 2017
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Unpaired image-to-image translation using cycle-consistent adversarial networks
Zhu, J.-Y.; Park, T.; Isola, P.; and Efros, A. A. 2017 · 2017
Earlier work this paper cites.
Generative adversarial networks
Goodfellow, I.; Pouget-Abadie, J.; Mirza, M.; Xu, B.; Warde-Farley, D.; Ozair, S.; Courville, A.; and Bengio, Y. 2020 · 2020
Earlier work this paper cites.
Denoising diffusion probabilistic models
Ho, J.; Jain, A.; and Abbeel, P. 2020 · 2020
Earlier work this paper cites.
Denoising Diffusion Implicit Models
Song, J.; Meng, C.; and Ermon, S. 2020 · 2020
Earlier work this paper cites.
Gradient surgery for multi-task learning
Yu, T.; Kumar, S.; Gupta, A.; Levine, S.; Hausman, K.; and Finn, C. 2020 · 2020
Earlier work this paper cites.
Clipscore: A reference-free evaluation metric for image captioning
Hessel, J.; Holtzman, A.; Forbes, M.; Bras, R. L.; and Choi, Y. 2021 · 2021
Earlier work this paper cites.
Generated faces in the wild: Quantitative comparison of stable diffusion, midjourney and dall-e 2
Borji, A. 2022 · 2022
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A survey of machine unlearning
Nguyen, T. T.; Huynh, T. T.; Nguyen, P. L.; Liew, A. W.-C.; Yin, H.; and Nguyen, Q. V. H. 2022 · 2022
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GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models
Nichol, A. Q.; Dhariwal, P.; Ramesh, A.; Shyam, P.; Mishkin, P.; Mcgrew, B.; Sutskever, I.; and Chen, M. 2022 · 2022
Earlier work this paper cites.
High-resolution image synthesis with latent diffusion models
Rombach, R.; Blattmann, A.; Lorenz, D.; Esser, P.; and Ommer, B. 2022 · 2022
Earlier work this paper cites.
Photorealistic text-to-image diffusion models with deep language understanding
Saharia, C.; Chan, W.; Saxena, S.; Li, L.; Whang, J.; Denton, E. L.; Ghasemipour, K.; Gontijo Lopes, R.; Karagol Ayan, B.; Salimans, T.; et al. 2022 · 2022
Earlier work this paper cites.
Laion-5b: An open large-scale dataset for training next generation image-text models
Schuhmann, C.; Beaumont, R.; Vencu, R.; Gordon, C.; Wightman, R.; Cherti, M.; Coombes, T.; Katta, A.; Mullis, C.; Wortsman, M.; et al. 2022 · 2022
Cited alongside, same era.
Membership inference attacks against text-to-image generation models
Wu, Y.; Yu, N.; Li, Z.; Backes, M.; and Zhang, Y. 2022 · 2022
Cited alongside, same era.
Extracting training data from diffusion models
Carlini, N.; Hayes, J.; Nasr, M.; Jagielski, M.; Sehwag, V.; Tramer, F.; Balle, B.; Ippolito, D.; and Wallace, E. 2023 · 2023
Cited alongside, same era.
Erasing concepts from diffusion models
Gandikota, R.; Materzynska, J.; Fiotto-Kaufman, J.; and Bau, D. 2023 · 2023
Cited alongside, same era.
Ablating concepts in text-to-image diffusion models
Kumari, N.; Zhang, B.; Wang, S.-Y.; Shechtman, E.; Zhang, R.; and Zhu, J.-Y. 2023 · 2023
Cited alongside, same era.
Semantic-Preserving Adversarial Example Attack against BERT
Gao, C.; Gu, K.; Vosoughi, S.; and Mehnaz, S. 2024a · 2024
Closest in time.
A Multi-scale Patch Approach with Diffusion Model for Image Dehazing
Guo, Y.; Wu, Y.; and Wan, C. 2024 · 2024
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Boosting Alignment for Post-Unlearning Text-to-Image Generative Models
Ko, M.; Li, H.; Wang, Z.; Patsenker, J.; Wang, J. T.; Li, Q.; Jin, M.; Song, D.; and Jia, R. 2024 · 2024
Closest in time.
Countering Personalized Text-to-Image Generation with Influence Watermarks
Liu, H.; Sun, Z.; and Mu, Y. 2024 · 2024
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Direct unlearning optimization for robust and safe text-to-image models
Park, Y.-H.; Yun, S.; Kim, J.-H.; Kim, J.; Jang, G.; Jeong, Y.; Jo, J.; and Lee, G. 2024 · 2024
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Trapdoor normalization with irreversible ownership verification
Liu, H.; Weng, Z.; Zhu, Y.; and Mu, Y. 2023 · 2023
Cited alongside, same era.
One-dimensional Adapter to Rule Them All: Concepts, Diffusion Models and Erasing Applications
Lyu, M.; Yang, Y.; Hong, H.; Chen, H.; Jin, X.; He, Y.; Xue, H.; Han, J.; and Ding, G. 2023 · 2023
Cited alongside, same era.
Responsible Innovation in the Age of Generative AI
Rao, D. 2023 · 2023
Cited alongside, same era.
Safe latent diffusion: Mitigating inappropriate degeneration in diffusion models
Schramowski, P.; Brack, M.; Deiseroth, B.; and Kersting, K. 2023 · 2023
Cited alongside, same era.
Anti-dreambooth: Protecting users from personalized text-to-image synthesis
Van Le, T.; Phung, H.; Nguyen, T. H.; Dao, Q.; Tran, N. N.; and Tran, A. 2023 · 2023
Cited alongside, same era.
Machine unlearning: A survey
Xu, H.; Zhu, T.; Zhang, L.; Zhou, W.; and Yu, P. S. 2023 · 2023
Cited alongside, same era.
Forget-me-not: Learning to forget in text-to-image diffusion models
Zhang, E.; Wang, K.; Xu, X.; Wang, Z.; and Shi, H. 2023 · 2023
Cited alongside, same era.
Singh, J.; Li, L.; Shi, W.; Krishna, R.; Choi, Y.; Koh, P. W.; Cohen, M. F.; Gould, S.; Zheng, L.; and Zettlemoyer, L. 2024 · 2024
Closest in time.
Attacks and defenses for generative diffusion models: A comprehensive survey
Truong, V. T.; Dang, L. B.; and Le, L. B. 2024 · 2024
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AEIOU: A Unified Defense Framework against NSFW Prompts in Text-to-Image Models
Wang, Y.; Chen, J.; Li, Q.; Yang, X.; and Ji, S. 2024 · 2024
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Safree: Training-free and adaptive guard for safe text-to-image and video generation
Yoon, J.; Yu, S.; Patil, V.; Yao, H.; and Bansal, M. 2024 · 2024
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Endowing Pre-trained Graph Models with Provable Fairness
Zhang, Z.; Zhang, M.; Yu, Y.; Yang, C.; Liu, J.; and Shi, C. 2024d · 2024
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On the Limitations and Prospects of Machine Unlearning for Generative AI
Zhou, S.; Wang, L.; Ye, J.; Wu, Y.; and Chang, H. 2024 · 2024
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Race: Robust adversarial concept erasure for secure text-to-image diffusion model
Kim, C.; Min, K.; and Yang, Y. 2025 · 2025
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Safeguard Text-to-Image Diffusion Models with Human Feedback Inversion
Kim, S.; Jung, S.; Kim, B.; Choi, M.; Shin, J.; and Lee, J. 2025 · 2025
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Learn to Optimize Denoising Scores: A Unified and Improved Diffusion Prior for 3D Generation
Yang, X.; Chen, Y.; Chen, C.; Zhang, C.; Xu, Y.; Yang, X.; Liu, F.; and Lin, G. 2025 · 2025
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To generate or not? safety-driven unlearned diffusion models are still easy to generate unsafe images… for now
Zhang, Y.; Jia, J.; Chen, X.; Chen, A.; Zhang, Y.; Liu, J.; Ding, K.; and Liu, S. 2025 · 2025
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