Boenisch, Franziska

42 publications

ICLRW 2025 Are Watermarks for Diffusion Models Radioactive? Jan Dubiński, Michel Meintz, Franziska Boenisch, Adam Dziedzic

ICLRW 2025 Beautiful Images, Toxic Words: Understanding and Addressing Offensive Text in Generated Images Aditya Kumar, Tom Blanchard, Adam Dziedzic, Franziska Boenisch

NeurIPS 2025 BitMark: Watermarking Bitwise Autoregressive Image Generative Models Louis Kerner, Michel Meintz, Bihe Zhao, Franziska Boenisch, Adam Dziedzic

CVPR 2025 CDI: Copyrighted Data Identification in Diffusion Models Jan Dubiński, Antoni Kowalczuk, Franziska Boenisch, Adam Dziedzic

ICLR 2025 Captured by Captions: On Memorization and Its Mitigation in CLIP Models Wenhao Wang, Adam Dziedzic, Grace C. Kim, Michael Backes, Franziska Boenisch

ICLRW 2025 Captured by Captions: On Memorization and Its Mitigation in CLIP Models Wenhao Wang, Adam Dziedzic, Grace C. Kim, Michael Backes, Franziska Boenisch

ICLRW 2025 DIET-PATE: Knowledge Transfer in PATE Without Public Data Michel Meintz, Adam Dziedzic, Franziska Boenisch

ICLR 2025 Differentially Private Federated Learning with Time-Adaptive Privacy Spending Shahrzad Kiani, Nupur Kulkarni, Adam Dziedzic, Stark Draper, Franziska Boenisch

AAAI 2025 Differentially Private Prototypes for Imbalanced Transfer Learning Dariush Wahdany, Matthew Jagielski, Adam Dziedzic, Franziska Boenisch

ICLRW 2025 Dp-Gpl: Differentially Private Graph Prompt Learning Jing Xu, Franziska Boenisch, Iyiola Emmanuel Olatunji, Adam Dziedzic

ICML 2025 Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes, Christopher A. Choquette-Choo, Adam Dziedzic

NeurIPS 2025 Exploring the Limits of Strong Membership Inference Attacks on Large Language Models Jamie Hayes, Ilia Shumailov, Christopher A. Choquette-Choo, Matthew Jagielski, Georgios Kaissis, Milad Nasr, Meenatchi Sundaram Muthu Selva Annamalai, Niloofar Mireshghallah, Igor Shilov, Matthieu Meeus, Yves-Alexandre de Montjoye, Katherine Lee, Franziska Boenisch, Adam Dziedzic, A. Feder Cooper

TMLR 2025 MUC: Machine Unlearning for Contrastive Learning with Black-Box Evaluation Yihan Wang, Yiwei Lu, Guojun Zhang, Franziska Boenisch, Adam Dziedzic, Yaoliang Yu, Xiao-Shan Gao

NeurIPS 2025 Memorization in Graph Neural Networks Adarsh Jamadandi, Jing Xu, Adam Dziedzic, Franziska Boenisch

ICLR 2025 Precise Parameter Localization for Textual Generation in Diffusion Models Łukasz Staniszewski, Bartosz Cywiński, Franziska Boenisch, Kamil Deja, Adam Dziedzic

ICML 2025 Privacy Attacks on Image AutoRegressive Models Antoni Kowalczuk, Jan Dubiński, Franziska Boenisch, Adam Dziedzic

ICLRW 2025 Privacy Attacks on Image AutoRegressive Models Antoni Kowalczuk, Jan Dubiński, Franziska Boenisch, Adam Dziedzic

ICLRW 2025 Privacy Auditing for Large Language Models with Natural Identifiers Lorenzo Rossi, Bartłomiej Marek, Franziska Boenisch, Adam Dziedzic

ICML 2025 Unlocking Post-Hoc Dataset Inference with Synthetic Data Bihe Zhao, Pratyush Maini, Franziska Boenisch, Adam Dziedzic

ICLRW 2025 Unlocking Post-Hoc Dataset Inference with Synthetic Data Bihe Zhao, Pratyush Maini, Franziska Boenisch, Adam Dziedzic

ICMLW 2024 Alignment Calibration: Machine Unlearning for Contrastive Learning Under Auditing Yihan Wang, Yiwei Lu, Guojun Zhang, Franziska Boenisch, Adam Dziedzic, Yaoliang Yu, Xiao-Shan Gao

NeurIPSW 2024 Auditing Empirical Privacy Protection of Private LLM Adaptations Lorenzo Rossi, Bartłomiej Marek, Vincent Hanke, Xun Wang, Michael Backes, Adam Dziedzic, Franziska Boenisch

TMLR 2024 Augment Then Smooth: Reconciling Differential Privacy with Certified Robustness Jiapeng Wu, Atiyeh Ashari Ghomi, David Glukhov, Jesse C. Cresswell, Franziska Boenisch, Nicolas Papernot

ICMLW 2024 Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks Antoni Kowalczuk, Jan Dubiński, Atiyeh Ashari Ghomi, Yi Sui, George Stein, Jiapeng Wu, Jesse C. Cresswell, Franziska Boenisch, Adam Dziedzic

NeurIPS 2024 Finding NeMo: Localizing Neurons Responsible for Memorization in Diffusion Models Dominik Hintersdorf, Lukas Struppek, Kristian Kersting, Adam Dziedzic, Franziska Boenisch

ICMLW 2024 Finding NeMo: Localizing Neurons Responsible for Memorization in Diffusion Models Lukas Struppek, Dominik Hintersdorf, Kristian Kersting, Adam Dziedzic, Franziska Boenisch

TMLR 2024 From Differential Privacy to Bounds on Membership Inference: Less Can Be More Anvith Thudi, Ilia Shumailov, Franziska Boenisch, Nicolas Papernot

NeurIPS 2024 Localizing Memorization in SSL Vision Encoders Wenhao Wang, Adam Dziedzic, Michael Backes, Franziska Boenisch

ICLR 2024 Memorization in Self-Supervised Learning Improves Downstream Generalization Wenhao Wang, Muhammad Ahmad Kaleem, Adam Dziedzic, Michael Backes, Nicolas Papernot, Franziska Boenisch

NeurIPS 2024 Open LLMs Are Necessary for Current Private Adaptations and Outperform Their Closed Alternatives Vincent Hanke, Tom Blanchard, Franziska Boenisch, Iyiola E. Olatunji, Michael Backes, Adam Dziedzic

ICMLW 2024 Open LLMs Are Necessary for Private Adaptations and Outperform Their Closed Alternatives Vincent Hanke, Tom Blanchard, Franziska Boenisch, Iyiola Emmanuel Olatunji, Michael Backes, Adam Dziedzic

ICMLW 2024 Open LLMs Are Necessary for Private Adaptations and Outperform Their Closed Alternatives Vincent Hanke, Tom Blanchard, Franziska Boenisch, Iyiola Emmanuel Olatunji, Michael Backes, Adam Dziedzic

ICMLW 2024 POST: A Framework for Privacy of Soft-Prompt Transfer Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes, Adam Dziedzic

ICMLW 2024 POST: A Framework for Privacy of Soft-Prompt Transfer Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes, Adam Dziedzic

ICLRW 2024 Personalized Differential Privacy for Ridge Regression Krishna Acharya, Franziska Boenisch, Rakshit Naidu, Juba Ziani

NeurIPS 2023 Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders Jan Dubiński, Stanisław Pawlak, Franziska Boenisch, Tomasz Trzcinski, Adam Dziedzic

NeurIPS 2023 Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models Haonan Duan, Adam Dziedzic, Nicolas Papernot, Franziska Boenisch

NeurIPS 2023 Have It Your Way: Individualized Privacy Assignment for DP-SGD Franziska Boenisch, Christopher Mühl, Adam Dziedzic, Roy Rinberg, Nicolas Papernot

NeurIPSW 2023 Learning to Walk Impartially on the Pareto Frontier of Fairness, Privacy, and Utility Mohammad Yaghini, Patty Liu, Franziska Boenisch, Nicolas Papernot

NeurIPSW 2023 Regulation Games for Trustworthy Machine Learning Mohammad Yaghini, Patty Liu, Franziska Boenisch, Nicolas Papernot

ICLRW 2023 Sentence Embedding Encoders Are Easy to Steal but Hard to Defend Adam Dziedzic, Franziska Boenisch, Mingjian Jiang, Haonan Duan, Nicolas Papernot

NeurIPS 2022 Dataset Inference for Self-Supervised Models Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem, Nikita Dhawan, Jonas Guan, Yannis Cattan, Franziska Boenisch, Nicolas Papernot