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Recent studies show that image and video generation models can be prompted to reproduce copyrighted content from their training data, raising serious legal concerns about copyright infringement.
A coefficient of agreement for nominal scales
Jacob Cohen · 1960
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The New Public Domain
Joseph P. Liu · 2013
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An overview of legal protection for fictional characters: Balancing public and private interests
Amanda Schreyer · 2015
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Matthew Sag · 2018
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Mickey Mouse Will Be in the Public Domain Soon—Here’s What That Means
Timothy B. Lee · 2019
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Language Models are Unsupervised Multitask Learners
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Extracting Training Data from Large Language Models
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The Pile: An 800gb dataset of diverse text for language modeling
Leo Gao, Stella Biderman, Sid Black, Laurence Golding, Travis Hoppe, Charles Foster, Jason Phang, Horace He, Anish Thite, Noa Nabeshima, et al · 2020
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Intellectual Property—Mickey Mouse’s Intellectual Property Adventure: What Disney’s War on Copyrights Has to Do with Trademarks and Patents
Kaitlyn Hennessey · 2020
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Fair learning
Mark A Lemley and Bryan Casey · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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Classifier-Free Diffusion Guidance
Jonathan Ho and Tim Salimans · 2021
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High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach, A. Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2021
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 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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In USENIX Security , 2023
Extracting training data from diffusion models, author=Carlini, Nicolas and Hayes, Jamie and Nasr, Milad and Jagielski, Matthew and Sehwag, Vikash and Tramer, Florian and Balle, Borja and Ippolito, Daphne and Wallace, Eric · 2023
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Improving Image Generation with Better Captions
James Betker, Gabriel Goh, Li Jing, Tim Brooks, Jianfeng Wang, Linjie Li, Long Ouyang, Juntang Zhuang, Joyce Lee, Yufei Guo, Wesam Manassra†, Prafulla Dhariwal†, Casey Chu, Yunxin Jiao, and Aditya Ramesh · 2023
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Stable video diffusion: Scaling latent video diffusion models to large datasets
Andreas Blattmann, Tim Dockhorn, Sumith Kulal, Daniel Mendelevitch, Maciej Kilian, Dominik Lorenz, Yam Levi, Zion English, Vikram Voleti, Adam Letts, et al · 2023
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Quantifying Memorization Across Neural Language Models
Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, and Chiyuan Zhang · 2023
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Hila Chefer, Yuval Alaluf, Yael Vinker, Lior Wolf, and Daniel Cohen-Or · 2023
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What’s In My Big Data?
Yanai Elazar, Akshita Bhagia, Ian Helgi Magnusson, Abhilasha Ravichander, Dustin Schwenk, Alane Suhr, Evan Pete Walsh, Dirk Groeneveld, Luca Soldaini, Sameer Singh, et al · 2023
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3:23-cv-00201, N.D. Cal. 2023
Andersen et al. v. Stability AI et al · 2023
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On provable copyright protection for generative models
Nikhil Vyas, Sham M Kakade, and Boaz Barak · 2023
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Forget-me-not: Learning to forget in text-to-image diffusion models
Eric Zhang, Kai Wang, Xingqian Xu, Zhangyang Wang, and Humphrey Shi · 2023
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PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis
Junsong Chen, Jincheng YU, Chongjian GE, Lewei Yao, Enze Xie, Zhongdao Wang, James Kwok, Ping Luo, Huchuan Lu, and Zhenguo Li · 2024
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Peter Henderson, Xuechen Li, Dan Jurafsky, Tatsunori Hashimoto, Mark A. Lemley, and Percy Liang · 2023
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Ablating Concepts in Text-to-Image Diffusion Models
Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman, Richard Zhang, and Jun-Yan Zhu · 2023
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VideoFusion: Decomposed Diffusion Models for High-Quality Video Generation
Zhengxiong Luo, Dayou Chen, Yingya Zhang, Yan Huang, Liang Wang, Yujun Shen, Deli Zhao, Jingren Zhou, and Tieniu Tan · 2023
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SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore
Sewon Min, Suchin Gururangan, Eric Wallace, Weijia Shi, Hannaneh Hajishirzi, Noah A Smith, and Luke Zettlemoyer · 2023
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Prompt Guide: Negative Prompts, 2023
Playground AI · 2023
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SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis
Dustin Podell, Zion English, Kyle Lacey, A. Blattmann, Tim Dockhorn, Jonas Muller, Joe Penna, and Robin Rombach · 2023
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Copyright safety for generative ai
Matthew Sag · 2023
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CPR: Retrieval Augmented Generation for Copyright Protection
Aditya Golatkar, Alessandro Achille, Luca Zancato, Yu-Xiang Wang, Ashwin Swaminathan, and Stefan 0 Soatto · 2024
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Reliable and Efficient Concept Erasure of Text-to-Image Diffusion Models, 2024
Chao Gong, Kai Chen, Zhipeng Wei, Jingjing Chen, and Yu-Gang Jiang · 2024
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Automatic Jailbreaking of the Text-to-Image Generative AI Systems
Minseon Kim, Hyomin Lee, Boqing Gong, Huishuai Zhang, and Sung Ju Hwang · 2024
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Talkin’ ’Bout AI Generation: Copyright and the Generative-AI Supply Chain, 2024
Katherine Lee, A. Feder Cooper, and James Grimmelmann · 2024
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Rui Ma, Qiang Zhou, Yizhu Jin, Daquan Zhou, Bangjun Xiao, Xiuyu Li, Yi Qu, Aishani Singh, Kurt Keutzer, Jingtong Hu, Xiaodong Xie, Zhen Dong, Shanghang Zhang, and Shiji Zhou · 2024
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Pat McGuinness · 2024
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Detecting Pretraining Data from Large Language Models
Weijia Shi, Anirudh Ajith, Mengzhou Xia, Yangsibo Huang, Daogao Liu, Terra Blevins, Danqi Chen, and Luke Zettlemoyer · 2024
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China Court Awards Damages Over AI Images Resembling Ultraman; Service Provider Held Liable For Copyright Infringement
The Yomiuri Shimbun · 2024
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Raccoon: Prompt Extraction Benchmark of LLM-Integrated Applications, 2024
Junlin Wang, Tianyi Yang, Roy Xie, and Bhuwan Dhingra · 2024
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