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Text-to-image (T2I) diffusion models have drawn attention for their ability to generate high-quality images with precise text alignment.
Uncovering the disentanglement capability in text-to-image diffusion models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 1900–1910
Qiucheng Wu, Yujian Liu, Handong Zhao, Ajinkya Kale, Trung Bui, Tong Yu, Zhe Lin, Yang Zhang, and Shiyu Chang. 2023 · 1910
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg S Corrado, and Jeff Dean. 2013 · 2013
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Microsoft coco: Common objects in context. In Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13 . Springer, 740–755
Tsung-Yi Lin, Michael Maire, Serge Belongie, James Hays, Pietro Perona, Deva Ramanan, Piotr Dollár, and C Lawrence Zitnick. 2014 · 2014
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Textbugger: Generating adversarial text against real-world applications
Jinfeng Li, Shouling Ji, Tianyu Du, Bo Li, and Ting Wang. 2018 · 2018
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The Unreasonable Effectiveness of Deep Features as a Perceptual Metric. In CVPR
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang. 2018 · 2018
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Nudenet: Neural nets for nudity classification, detection and selective censoring
Bedapudi Praneeth. 2019 · 2019
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy. 2020 · 2020
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Bae: Bert-based adversarial examples for text classification
Siddhant Garg and Goutham Ramakrishnan. 2020 · 2020
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Is bert really robust? a strong baseline for natural language attack on text classification and entailment. In Proceedings of the AAAI conference on artificial intelligence , Vol. 34. 8018–8025
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits. 2020 · 2020
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Datasheets for datasets
Timnit Gebru, Jamie Morgenstern, Briana Vecchione, Jennifer Wortman Vaughan, Hanna Wallach, Hal Daumé Iii, and Kate Crawford. 2021 · 2021
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
Alex Nichol, Prafulla Dhariwal, Aditya Ramesh, Pranav Shyam, Pamela Mishkin, Bob McGrew, Ilya Sutskever, and Mark Chen. 2021 · 2021
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Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
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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High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2021 · 2021
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OpenAI. DALL-E 2 preview - risks and limitations
2022 · 2022
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Red teaming language models to reduce harms: Methods, scaling behaviors, and lessons learned
Deep Ganguli, Liane Lovitt, Jackson Kernion, Amanda Askell, Yuntao Bai, Saurav Kadavath, Ben Mann, Ethan Perez, Nicholas Schiefer, Kamal Ndousse, et al · 2022
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Stable diffusion 1 vs 2 - what you need to know
Ryan O’Connor. 2022 · 2022
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Red teaming language models with language models
Ethan Perez, Saffron Huang, Francis Song, Trevor Cai, Roman Ring, John Aslanides, Amelia Glaese, Nat McAleese, and Geoffrey Irving. 2022 · 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 · 2022
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Red-teaming the stable diffusion safety filter
Javier Rando, Daniel Paleka, David Lindner, Lennart Heim, and Florian Tramèr. 2022 · 2022
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High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition . 10684–10695
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. 2022 · 2022
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Robin Rombach and Patrick Esser. Stable diffusion v2 model card
Robin Rombach and Patrick Esser. 2022 · 2022
Cited alongside, same era.
Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily L Denton, Kamyar Ghasemipour, Raphael Gontijo Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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Can Machines Help Us Answering Question 16 in Datasheets, and In Turn Reflecting on Inappropriate Content?. In Proceedings of the ACM Conference on Fairness, Accountability, and Transparency (FAccT)
Patrick Schramowski, Christopher Tauchmann, and Kristian Kersting. 2022 · 2022
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Laion-5b: An open large-scale dataset for training next generation image-text models
Christoph Schuhmann, Romain Beaumont, Richard Vencu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al · 2022
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Leonardo ai content moderation filter: Everything you need to know
2023 · 2023
Midjourney
2024 · 2024
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Unified concept editing in diffusion models. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision . 5111–5120
Rohit Gandikota, Hadas Orgad, Yonatan Belinkov, Joanna Materzyńska, and David Bau. 2024 · 2024
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Reliable and efficient concept erasure of text-to-image diffusion models
Chao Gong, Kai Chen, Zhipeng Wei, Jingjing Chen, and Yu-Gang Jiang. 2024 · 2024
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SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?
Hasan Abed Al Kader Hammoud, Hani Itani, Fabio Pizzati, Philip Torr, Adel Bibi, and Bernard Ghanem. 2024 · 2024
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Receler: Reliable concept erasing of text-to-image diffusion models via lightweight erasers. In European Conference on Computer Vision . Springer, 360–376
Chi-Pin Huang, Kai-Po Chang, Chung-Ting Tsai, Yung-Hsuan Lai, Fu-En Yang, and Yu-Chiang Frank Wang. 2024 · 2024
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Cited alongside, same era.
Prompting4debugging: Red-teaming text-to-image diffusion models by finding problematic prompts
Zhi-Yi Chin, Chieh-Ming Jiang, Ching-Chun Huang, Pin-Yu Chen, and Wei-Chen Chiu. 2023 · 2023
Cited alongside, same era.
Erasing concepts from diffusion models. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 2426–2436
Rohit Gandikota, Joanna Materzynska, Jaden Fiotto-Kaufman, and David Bau. 2023 · 2023
Cited alongside, same era.
Lm-switch: Lightweight language model conditioning in word embedding space
Chi Han, Jialiang Xu, Manling Li, Yi Fung, Chenkai Sun, Nan Jiang, Tarek Abdelzaher, and Heng Ji. 2023 · 2023
Cited alongside, same era.
Ablating concepts in text-to-image diffusion models. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 22691–22702
Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, and Jun-Yan Zhu. 2023 · 2023
Cited alongside, same era.
A holistic approach to undesired content detection in the real world. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 37. 15009–15018
Todor Markov, Chong Zhang, Sandhini Agarwal, Florentine Eloundou Nekoul, Theodore Lee, Steven Adler, Angela Jiang, and Lilian Weng. 2023 · 2023
Cited alongside, same era.
Black box adversarial prompting for foundation models
Natalie Maus, Patrick Chao, Eric Wong, and Jacob Gardner. 2023 · 2023
Cited alongside, same era.
Editing implicit assumptions in text-to-image diffusion models. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 7053–7061
Hadas Orgad, Bahjat Kawar, and Yonatan Belinkov. 2023 · 2023
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Race: Robust adversarial concept erasure for secure text-to-image diffusion model. In European Conference on Computer Vision . Springer, 461–478
Changhoon Kim, Kyle Min, and Yezhou Yang. 2024 · 2024
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ART: Automatic Red-teaming for Text-to-Image Models to Protect Benign Users
Guanlin Li, Kangjie Chen, Shudong Zhang, Jie Zhang, and Tianwei Zhang. 2024 · 2024
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Latent guard: a safety framework for text-to-image generation
Runtao Liu, Ashkan Khakzar, Jindong Gu, Qifeng Chen, Philip Torr, and Fabio Pizzati. 2024 · 2024
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Mace: Mass concept erasure in diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 6430–6440
Shilin Lu, Zilan Wang, Leyang Li, Yanzhu Liu, and Adams Wai-Kin Kong. 2024 · 2024
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One-dimensional Adapter to Rule Them All: Concepts Diffusion Models and Erasing Applications. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 7559–7568
Mengyao Lyu, Yuhong Yang, Haiwen Hong, Hui Chen, Xuan Jin, Yuan He, Hui Xue, Jungong Han, and Guiguang Ding. 2024 · 2024
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Jailbreaking Prompt Attack: A Controllable Adversarial Attack against Diffusion Models
Jiachen Ma, Anda Cao, Zhiqing Xiao, Jie Zhang, Chao Ye, and Junbo Zhao. 2024 · 2024
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Localization and manipulation of immoral visual cues for safe text-to-image generation. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision . 4675–4684
Seongbeom Park, Suhong Moon, Seunghyun Park, and Jinkyu Kim. 2024 · 2024
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Erasediff: Erasing data influence in diffusion models
Jing Wu, Trung Le, Munawar Hayat, and Mehrtash Harandi. 2024 · 2024
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Sneakyprompt: Jailbreaking text-to-image generative models. In 2024 IEEE symposium on security and privacy (SP) . IEEE, 897–912
Yuchen Yang, Bo Hui, Haolin Yuan, Neil Gong, and Yinzhi Cao. 2024b · 2024
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SAFREE: Training-Free and Adaptive Guard for Safe Text-to-Image And Video Generation
Jaehong Yoon, Shoubin Yu, Vaidehi Patil, Huaxiu Yao, and Mohit Bansal. 2024 · 2024
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Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, and Sijia Liu. 2024a · 2024
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Distorting Embedding Space for Safety: A Defense Mechanism for Adversarially Robust Diffusion Models
Jaesin Ahn and Heechul Jung. 2025 · 2025
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Aligning Diffusion Model with Problem Constraints for Trajectory Optimization
Anjian Li and Ryne Beeson. 2025 · 2025
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ChatGPT: Language model (June 16 version)
OpenAI. 2023 · 2025
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