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The advent of artificial intelligence-generated content (AIGC) represents a pivotal moment in the evolution of information technology.
Deep learning with differential privacy. In Proceedings of the 2016 ACM SIGSAC conference on computer and communications security . 308–318
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TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation. In Findings of the Association for Computational Linguistics: EMNLP 2021 . 2001–2016
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Attributing fake images to gans: Learning and analyzing gan fingerprints. In Proceedings of the IEEE/CVF international conference on computer vision . 7556–7566
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Generative adversarial networks
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A non-parametric test to detect data-copying in generative models. In International Conference on Artificial Intelligence and Statistics
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Media forensics and deepfakes: an overview
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Persistent anti-muslim bias in large language models. In Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society . 298–306
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On the dangers of stochastic parrots: Can language models be too big?. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency . 610–623
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Multimodal datasets: misogyny, pornography, and malignant stereotypes
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Machine unlearning. In 2021 IEEE Symposium on Security and Privacy (SP) . IEEE, 141–159
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Generating mobility trajectories with retained Data Utility. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining . 2610–2620
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Extracting training data from large language models. In 30th USENIX Security Symposium (USENIX Security 21) . 2633–2650
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Perceptual indistinguishability-net (pi-net): Facial image obfuscation with manipulable semantics. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 6478–6487
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Truthful AI: Developing and governing AI that does not lie
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TweepFake: About detecting deepfake tweets
Tiziano Fagni, Fabrizio Falchi, Margherita Gambini, Antonio Martella, and Maurizio Tesconi. 2021 · 2021
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When do gans replicate? on the choice of dataset size. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 6701–6710
Qianli Feng, Chenqi Guo, Fabian Benitez-Quiroz, and Aleix M Martinez. 2021 · 2021
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Towards discovery and attribution of open-world gan generated images. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 14094–14103
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Artificial Intelligence Security: Threats and Countermeasures
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Adversarial Deepfakes: Evaluating Vulnerability of Deepfake Detectors to Adversarial Examples. In 2021 IEEE Winter Conference on Applications of Computer Vision (WACV) . 3347–3356
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When Machine Learning Meets Privacy: A Survey and Outlook
Bo Liu, Ming Ding, Sina Shaham, Wenny Rahayu, Farhad Farokhi, and Zihuai Lin. 2021 · 2021
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The creation and detection of deepfakes: A survey
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Glide: Towards photorealistic image generation and editing with text-guided diffusion models
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Attack as the best defense: Nullifying image-to-image translation gans via limit-aware adversarial attack. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 16188–16197
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Artificial fingerprinting for generative models: Rooting deepfake attribution in training data. In Proceedings of the IEEE/CVF International conference on computer vision . 14448–14457
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Clip retrieval system
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DALL·E 2 pre-training mitigations
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How faithful is your synthetic data? sample-level metrics for evaluating and auditing generative models. In International Conference on Machine Learning . PMLR, 290–306
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VR, Deepfakes and Epistemic Security. In 2022 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) . 93–98
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Reducing Training Sample Memorization in GANs by Training with Memorization Rejection
Andrew Bai, Cho-Jui Hsieh, Wendy Kan, and Hsuan-Tien Lin. 2022 · 2022
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Repmix: Representation mixing for robust attribution of synthesized images. In European Conference on Computer Vision . Springer, 146–163
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Differentially private diffusion models
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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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Pile of law: Learning responsible data filtering from the law and a 256gb open-source legal dataset
Peter Henderson, Mark Krass, Lucia Zheng, Neel Guha, Christopher D Manning, Dan Jurafsky, and Daniel Ho. 2022 · 2022
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Deduplicating training data mitigates privacy risks in language models. In International Conference on Machine Learning . PMLR, 10697–10707
Nikhil Kandpal, Eric Wallace, and Colin Raffel. 2022 · 2022
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Factuality enhanced language models for open-ended text generation
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Privacy-preserving synthetic data generation for recommendation systems. In Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval . 1379–1389
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You Are What You Write: Preserving Privacy in the Era of Large Language Models
Richard Plant, Valerio Giuffrida, and Dimitra Gkatzia. 2022 · 2022
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Red-teaming the stable diffusion safety filter
Javier Rando, Daniel Paleka, David Lindner, Lennard Heim, and Florian Tramèr. 2022 · 2022
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SynSciPass: detecting appropriate uses of scientific text generation
Domenic Rosati. 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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SinGAN-Seg: Synthetic training data generation for medical image segmentation
Vajira Thambawita, Pegah Salehi, Sajad Amouei Sheshkal, Steven A Hicks, Hugo L Hammer, Sravanthi Parasa, Thomas de Lange, Pål Halvorsen, and Michael A Riegler. 2022 · 2022
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Memorization without overfitting: Analyzing the training dynamics of large language models
Kushal Tirumala, Aram Markosyan, Luke Zettlemoyer, and Armen Aghajanyan. 2022 · 2022
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A survey on metaverse: Fundamentals, security, and privacy
Yuntao Wang, Zhou Su, Ning Zhang, Rui Xing, Dongxiao Liu, Tom H Luan, and Xuemin Shen. 2022b · 2022
Cited alongside, same era.
Diffusiondb: A large-scale prompt gallery dataset for text-to-image generative models
Zijie J Wang, Evan Montoya, David Munechika, Haoyang Yang, Benjamin Hoover, and Duen Horng Chau. 2022a · 2022
Cited alongside, same era.
Identitydp: Differential private identification protection for face images
Yunqian Wen, Bo Liu, Ming Ding, Rong Xie, and Li Song. 2022 · 2022
Cited alongside, same era.
Deepfake network architecture attribution. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 36. 4662–4670
Tianyun Yang, Ziyao Huang, Juan Cao, Lei Li, and Xirong Li. 2022 · 2022
De-fake: Detection and attribution of fake images generated by text-to-image generation models. In Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security . 3418–3432
Zeyang Sha, Zheng Li, Ning Yu, and Yang Zhang. 2023 · 2023
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Glaze: Protecting Artists from Style Mimicry by { \{ Text-to-Image } \} Models. In 32nd USENIX Security Symposium (USENIX Security 23) . 2187–2204
Shawn Shan, Jenna Cryan, Emily Wenger, Haitao Zheng, Rana Hanocka, and Ben Y Zhao. 2023 · 2023
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Diffusion art or digital forgery? investigating data replication in diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 6048–6058
Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, and Tom Goldstein. 2023 · 2023
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Waterbench: Towards holistic evaluation of watermarks for large language models
Shangqing Tu, Yuliang Sun, Yushi Bai, Jifan Yu, Lei Hou, and Juanzi Li. 2023 · 2023
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Cited alongside, same era.
On generating identifiable virtual faces. In Proceedings of the 30th ACM International Conference on Multimedia . 1465–1473
Zhuowen Yuan, Zhengxin You, Sheng Li, Zhenxing Qian, Xinpeng Zhang, and Alex Kot. 2022 · 2022
Cited alongside, same era.
Visual privacy attacks and defenses in deep learning: a survey
Guangsheng Zhang, Bo Liu, Tianqing Zhu, Andi Zhou, and Wanlei Zhou. 2022 · 2022
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Detecting Images Generated by Deep Diffusion Models Using Their Local Intrinsic Dimensionality. In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops . 448–459
2023 · 2023
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Disinformation Researchers Raise Alarms About A.I. Chatbots
2023 · 2023
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Fact Check: Was There an Explosion at the Pentagon?
2023 · 2023
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Interim Regulation on the Management of Generative Artificial intelligence (AI) Services
2023 · 2023
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The internal state of an llm knows when its lying
Amos Azaria and Tom Mitchell. 2023 · 2023
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Anti-DreamBooth: Protecting users from personalized text-to-image synthesis. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 2116–2127
Thanh Van Le, Hao Phung, Thuan Hoang Nguyen, Quan Dao, Ngoc N Tran, and Anh Tran. 2023 · 2023
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Ghostbuster: Detecting text ghostwritten by large language models
Vivek Verma, Eve Fleisig, Nicholas Tomlin, and Dan Klein. 2023 · 2023
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Survey on factuality in large language models: Knowledge, retrieval and domain-specificity
Cunxiang Wang, Xiaoze Liu, Yuanhao Yue, Xiangru Tang, Tianhang Zhang, Cheng Jiayang, Yunzhi Yao, Wenyang Gao, Xuming Hu, Zehan Qi, et al · 2023
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Identifiable Face Privacy Protection via Virtual Identity Transformation
Tao Wang, Yushu Zhang, Ruoyu Zhao, Wenying Wen, and Rushi Lan. 2023d · 2023
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A Reproducible Extraction of Training Images from Diffusion Models
Ryan Webster. 2023 · 2023
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Divide and conquer: a two-step method for high quality face de-identification with model explainability. In Proceedings of the IEEE/CVF International Conference on Computer Vision . 5148–5157
Yunqian Wen, Bo Liu, Jingyi Cao, Rong Xie, and Li Song. 2023 · 2023
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Towards Prompt-robust Face Privacy Protection via Adversarial Decoupling Augmentation Framework
Ruijia Wu, Yuhang Wang, Huafeng Shi, Zhipeng Yu, Yichao Wu, and Ding Liang. 2023 · 2023
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Ai-generated image detection using a cross-attention enhanced dual-stream network. In 2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) . IEEE, 1463–1470
Ziyi Xi, Wenmin Huang, Kangkang Wei, Weiqi Luo, and Peijia Zheng. 2023 · 2023
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Flexible and Secure Watermarking for Latent Diffusion Model. In Proceedings of the 31st ACM International Conference on Multimedia (<conf-loc>, <city>Ottawa ON</city>, <country>Canada</country>, </conf-loc>) (MM ’23) . Association for Computing Machinery, New York, NY, USA, 1668–1676
Cheng Xiong, Chuan Qin, Guorui Feng, and Xinpeng Zhang. 2023 · 2023
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DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection. In Advances in Neural Information Processing Systems , Vol. 36. Curran Associates, Inc., 4534–4565
Zhiyuan Yan, Yong Zhang, Xinhang Yuan, Siwei Lyu, and Baoyuan Wu. 2023 · 2023
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Progressive Open Space Expansion for Open-Set Model Attribution. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 15856–15865
Tianyun Yang, Danding Wang, Fan Tang, Xinying Zhao, Juan Cao, and Sheng Tang. 2023 · 2023
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PPUP-GAN: A GAN-based privacy-protecting method for aerial photography
Zhexin Yao, Qiuming Liu, Jingkang Yang, Yanan Chen, and Zhen Wu. 2023 · 2023
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Securing Deep Generative Models with Universal Adversarial Signature
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A recipe for watermarking diffusion models
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Rich and Poor Texture Contrast: A Simple yet Effective Approach for AI-generated Image Detection
Nan Zhong, Yiran Xu, Zhenxing Qian, and Xinpeng Zhang. 2023 · 2023
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Information-Containing Adversarial Perturbation for Combating Facial Manipulation Systems
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WAVES: Benchmarking the Robustness of Image Watermarks. In Proceedings of the 41st International Conference on Machine Learning (ICML) , Vol. 235. 1456–1492
Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, and Furong Huang. 2024 · 2024
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ProMark: Proactive Diffusion Watermarking for Causal Attribution. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) . 10802–10811
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Cifake: Image classification and explainable identification of ai-generated synthetic images
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Into the LAION’s Den: Investigating hate in multimodal datasets
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A revolution of personalized healthcare: Enabling human digital twin with mobile AIGC
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CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing. In The Twelfth International Conference on Learning Representations
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Level up the deepfake detection: a method to effectively discriminate images generated by gan architectures and diffusion models. In Intelligent Systems Conference . Springer, 615–625
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Mgtbench: Benchmarking machine-generated text detection. In The ACM Conference on Computer and Communications Security
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Double Face: Leveraging User Intelligence to Characterize and Recognize AI-synthesized Faces. In 33rd USENIX Security Symposium (USENIX Security 24) . Philadelphia, PA, 1009–1026
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Detecting multimedia generated by large ai models: A survey
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Detecting Voice Cloning Attacks via Timbre Watermarking. In Network and Distributed System Security Symposium
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Semantic communications for artificial intelligence generated content (AIGC) toward effective content creation
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Blockchain-Empowered Lifecycle Management for AI-Generated Content Products in Edge Networks
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Towards Message Brokers for Generative AI: Survey, Challenges, and Opportunities
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Deep image fingerprint: Towards low budget synthetic image detection and model lineage analysis. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision . 4067–4076
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GenderCARE: A Comprehensive Framework for Assessing and Reducing Gender Bias in Large Language Models. In ACM Conference on Computer and Communications Security(CCS 24)
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Intrinsic dimension estimation for robust detection of ai-generated texts
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Seeing is not Believing: An Identity Hider for Human Vision Privacy Protection
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Quantifying Privacy Risks of Prompts in Visual Prompt Learning. In 33rd USENIX Security Symposium (USENIX Security 24) . Philadelphia, PA, 5841–5858
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Unleashing the power of edge-cloud generative ai in mobile networks: A survey of aigc services
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Leandojo: Theorem proving with retrieval-augmented language models
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PromptCARE: Prompt Copyright Protection by Watermark Injection and Verification. In IEEE Symposium on Security and Privacy (S&P) . IEEE
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LLM-as-a-Coauthor: Can Mixed Human-Written and Machine-Generated Text Be Detected?. In Findings of the Association for Computational Linguistics: NAACL 2024 . 409–436
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Proactive image manipulation detection via deep semi-fragile watermark
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