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Recent research has seen significant interest in methods for concept removal and targeted forgetting in text-to-image diffusion models.
Reverse-time diffusion equation models
Brian DO Anderson · 1982
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Facenet: A unified embedding for face recognition and clustering
Florian Schroff, Dmitry Kalenichenko, and James Philbin · 2015
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Generative adversarial networks: introduction and outlook
Kunfeng Wang, Chao Gou, Yanjie Duan, Yilun Lin, Xinhu Zheng, and Fei-Yue Wang · 2017
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Mikolaj Binkowski, Danica J. Sutherland, M. Arbel, and A. Gretton · 2018
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Gans trained by a two time-scale update rule converge to a local nash equilibrium, 2018
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2018
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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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Certified data removal from machine learning models
Chuan Guo, Tom Goldstein, Awni Hannun, and Laurens Van Der Maaten · 2019
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Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Machine unlearning
Lucas Bourtoule, Varun Chandrasekaran, Christopher A Choquette-Choo, Hengrui Jia, Adelin Travers, Baiwu Zhang, David Lie, and Nicolas Papernot · 2021
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Diffusion models beat gans on image synthesis
Prafulla Dhariwal and Alexander Nichol · 2021
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Clipscore: A reference-free evaluation metric for image captioning
Jack Hessel, Ari Holtzman, Maxwell Forbes, Ronan Le Bras, and Yejin Choi · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Score-based generative modeling in latent space
Arash Vahdat, Karsten Kreis, and Jan Kautz · 2021
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Score-based generative modeling of graphs via the system of stochastic differential equations
Jaehyeong Jo, Seul Lee, and Sung Ju Hwang · 2022
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Denoising diffusion restoration models
Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song · 2022
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A survey of machine unlearning
Thanh Tam Nguyen, Thanh Trung Huynh, Phi Le Nguyen, Alan Wee-Chung Liew, Hongzhi Yin, and Quoc Viet Hung Nguyen · 2022
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A self-supervised descriptor for image copy detection
Ed Pizzi, Sreya Dutta Roy, Sugosh Nagavara Ravindra, Priya Goyal, and Matthijs Douze · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Algorithms that approximate data removal: New results and limitations
Vinith Suriyakumar and Ashia C Wilson · 2022
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Dynamic prompt learning: Addressing cross-attention leakage for text-based image editing
Fei Yang, Shiqi Yang, Muhammad Atif Butt, Joost van de Weijer, et al · 2023
Later among the works it cites.
Salun: Empowering machine unlearning via gradient-based weight saliency in both image classification and generation
Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, and Sijia Liu · 2024
Closest in time.
Okkhor-diffusion: Class guided generation of bangla isolated handwritten characters using denoising diffusion probabilistic model (ddpm)
Md Mubtasim Fuad, A Faiyaz, Noor Mairukh Khan Arnob, MF Mridha, Aloke Kumar Saha, and Zeyar Aung · 2024
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Erasing concepts from text-to-image diffusion models with few-shot unlearning
Masane Fuchi and Tomohiro Takagi · 2024
Closest in time.
Unified concept editing in diffusion models
Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzyńska, and David Bau · 2024
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Youngsik Yoon, Jinhwan Nam, Hyojeong Yun, Jaeho Lee, Dongwoo Kim, and Jungseul Ok · 2022
Cited alongside, same era.
Extracting training data from diffusion models
Nicolas Carlini, Jamie Hayes, Milad Nasr, Matthew Jagielski, Vikash Sehwag, Florian Tramer, Borja Balle, Daphne Ippolito, and Eric Wallace · 2023
Cited alongside, same era.
Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, and Sijia Liu · 2023
Cited alongside, same era.
Erasing concepts from diffusion models
Rohit Gandikota, Joanna Materzynska, Jaden Fiotto-Kaufman, and David Bau · 2023
Cited alongside, same era.
Matryoshka diffusion models
Jiatao Gu, Shuangfei Zhai, Yizhe Zhang, Joshua M Susskind, and Navdeep Jaitly · 2023
Cited alongside, same era.
Towards safe self-distillation of internet-scale text-to-image diffusion models, 2023
Sanghyun Kim, Seohyeon Jung, Balhae Kim, Moonseok Choi, Jinwoo Shin, and Juho Lee · 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.
Closest in time.
Probing unlearned diffusion models: A transferable adversarial attack perspective
Xiaoxuan Han, Songlin Yang, Wei Wang, Yang Li, and Jing Dong · 2024
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Selective amnesia: A continual learning approach to forgetting in deep generative models
Alvin Heng and Harold Soh · 2024
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All but one: Surgical concept erasing with model preservation in text-to-image diffusion models
Seunghoo Hong, Juhun Lee, and Simon S Woo · 2024
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Safegen: Mitigating sexually explicit content generation in text-to-image models
Xinfeng Li, Yuchen Yang, Jiangyi Deng, Chen Yan, Yanjiao Chen, Xiaoyu Ji, and Wenyuan Xu · 2024
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Faster diffusion via temporal attention decomposition
Haozhe Liu, Wentian Zhang, Jinheng Xie, Francesco Faccio, Mengmeng Xu, Tao Xiang, Mike Zheng Shou, Juan-Manuel Perez-Rua, and Jürgen Schmidhuber · 2024
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Mace: Mass concept erasure in diffusion models
Shilin Lu, Zilan Wang, Leyang Li, Yanzhu Liu, and Adams Wai-Kin Kong · 2024
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Star-shaped denoising diffusion probabilistic models
Andrey Okhotin, Dmitry Molchanov, Arkhipkin Vladimir, Grigory Bartosh, Viktor Ohanesian, Aibek Alanov, and Dmitry P Vetrov · 2024
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Multi-modal recommendation unlearning
Yash Sinha, Murari Mandal, and Mohan Kankanhalli · 2024
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Denoising diffusion probabilistic models in six simple steps
Richard E Turner, Cristiana-Diana Diaconu, Stratis Markou, Aliaksandra Shysheya, Andrew YK Foong, and Bruno Mlodozeniec · 2024
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Mma-diffusion: Multimodal attack on diffusion models
Yijun Yang, Ruiyuan Gao, Xiaosen Wang, Tsung-Yi Ho, Nan Xu, and Qiang Xu · 2024
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Domain-adaptive hrrp generation using two-stage denoising diffusion probability model
Qiang Zhou, Yanhua Wang, Xin Zhang, Liang Zhang, and Teng Long · 2024
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