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Diffusion models have demonstrated remarkable capability in generating high-quality visual content from textual descriptions.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
Earlier work this paper cites.
Decision-based adversarial attacks: Reliable attacks against black-box machine learning models
Wieland Brendel, Jonas Rauber, and Matthias Bethge · 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
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Nudenet: Neural nets for nudity classification, detection and selective censorin
Bedapudi Praneet · 2019
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The emergence of deepfake technology: A review
Mika Westerlund · 2019
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Adapterfusion: Non-destructive task composition for transfer learning
Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé, Kyunghyun Cho, and Iryna Gurevych · 2020
Earlier work this paper cites.
The power of scale for parameter-efficient prompt tuning
Brian Lester, Rami Al-Rfou, and Noah Constant · 2021
Earlier work this paper cites.
Prefix-tuning: Optimizing continuous prompts for generation
Xiang Lisa Li and Percy Liang · 2021
Earlier work this paper cites.
Zero-shot text-to-image generation
Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever · 2021
Earlier work this paper cites.
K-adapter: Infusing knowledge into pre-trained models with adapters, 2021
Ruize Wang, Duyu Tang, Nan Duan, Zhongyu Wei, Xuanjing Huang, Jianshu Ji, Guihong Cao, Daxin Jiang, and Ming Zhou · 2021
Cited alongside, same era.
An image is worth one word: Personalizing text-to-image generation using textual inversion
Rinon Gal, Yuval Alaluf, Yuval Atzmon, Or Patashnik, Amit H Bermano, Gal Chechik, and Daniel Cohen-Or · 2022
Cited alongside, same era.
Lora: Low-rank adaptation of large language models
Edward J. Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2022
Cited alongside, same era.
Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
Cited alongside, same era.
Red-teaming the stable diffusion safety filter
Javier Rando et al · 2022
Cited alongside, same era.
Editing implicit assumptions in text-to-image diffusion models
Hadas Orgad, Bahjat Kawar, and Yonatan Belinkov · 2023
Later among the works it cites.
Unsafe diffusion: On the generation of unsafe images and hateful memes from text-to-image models
Yiting Qu, Xinyue Shen, Xinlei He, Michael Backes, Savvas Zannettou, and Yang Zhang · 2023
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2023
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Safe latent diffusion: Mitigating inappropriate degeneration in diffusion models
Patrick Schramowski et al · 2023
Later among the works it cites.
Anti-dreambooth: Protecting users from personalized text-to-image synthesis
Thanh Van Le, Hao Phung, Thuan Hoang Nguyen, Quan Dao, Ngoc N Tran, and Anh Tran · 2023
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
Cited alongside, same era.
Stable diffusion 2.0 release
StabilityAI · 2022
Cited alongside, same era.
What the daam: Interpreting stable diffusion using cross attention
Raphael Tang, Linqing Liu, Akshat Pandey, Zhiying Jiang, Gefei Yang, Karun Kumar, Pontus Stenetorp, Jimmy Lin, and Ferhan Ture · 2022
Cited alongside, same era.
Erasing concepts from diffusion models
Rohit Gandikota et al · 2023
Cited alongside, same era.
Ablating concepts in text-to-image diffusion models
Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, and Jun-Yan Zhu · 2023
Cited alongside, same era.
Eric Zhang et al · 2023
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Erasing undesirable concepts in diffusion models with adversarial preservation
Anh Bui, Long Vuong, Khanh Doan, Trung Le, Paul Montague, Tamas Abraham, and Dinh Phung · 2024
Closest in time.
Unified concept editing in diffusion models
Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzyńska, and David Bau · 2024
Closest in time.
Sneakyprompt: Jailbreaking text-to-image generative models
Yuchen Yang, Bo Hui, Haolin Yuan, Neil Gong, and Yinzhi Cao · 2024
Closest in time.
Fantastic targets for concept erasure in diffusion models and where to find them
Anh Bui, Trang Vu, Long Vuong, Trung Le, Paul Montague, Tamas Abraham, and Dinh Phung · 2025
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