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Franziska Boenisch · SciRah

Researcher profile · Semantic Scholar

Franziska Boenisch

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Franziska Boenisch — researcher profile on SciRah

h-index: 14
Works: 62
Citations: 958

Most-cited papers

When the Curious Abandon Honesty: Federated Learning Is Not Private
Franziska Boenisch, Adam Dziedzic, R. Schuster, A. Shamsabadi +2 more
2021European Symposium on Security and Privacy256 citations Open access
Semantic Scholar
Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models
Haonan Duan, Adam Dziedzic, Nicolas Papernot, Franziska Boenisch
2023Neural Information Processing Systems120 citations Open access
Semantic Scholar
On the Privacy Risk of In-context Learning
Haonan Duan, Adam Dziedzic, Mohammad Yaghini, Nicolas Papernot +1 more
2024arXiv.org75 citations
Semantic Scholar
Dataset Inference for Self-Supervised Models
Adam Dziedzic, Haonan Duan, Muhammad Ahmad Kaleem, Nikita Dhawan +4 more
2022Neural Information Processing Systems60 citations Open access
Semantic Scholar
Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models
Dominik Hintersdorf, Lukas Struppek, K. Kersting, Adam Dziedzic +1 more
2024Neural Information Processing Systems47 citations
Semantic Scholar
Have it your way: Individualized Privacy Assignment for DP-SGD
Franziska Boenisch, Christopher Muhl, Adam Dziedzic, Roy Rinberg +1 more
2023Neural Information Processing Systems41 citations Open access
Semantic Scholar
Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation
Franziska Boenisch, Adam Dziedzic, R. Schuster, A. Shamsabadi +2 more
2023European Symposium on Security and Privacy38 citations Open access
Semantic Scholar
Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives
Vincent Hanke, Tom Blanchard, Franziska Boenisch, I. E. Olatunji +2 more
2024Neural Information Processing Systems27 citations
Semantic Scholar
Exploring the limits of strong membership inference attacks on large language models
Jamie Hayes, Ilia Shumailov, Christopher A. Choquette-Choo, Matthew Jagielski +11 more
2025Neural Information Processing Systems25 citations
Semantic Scholar
Individualized PATE: Differentially Private Machine Learning with Individual Privacy Guarantees
Franziska Boenisch, Christopher Muhl, Roy Rinberg, Jannis Ihrig +1 more
2022Proceedings on Privacy Enhancing Technologies24 citations Open access
Semantic Scholar
Memorization in Self-Supervised Learning Improves Downstream Generalization
Wen-Hao Wang, Muhammad Ahmad Kaleem, Adam Dziedzic, Michael Backes +2 more
2024International Conference on Learning Representations23 citations
Semantic Scholar
Bounding Membership Inference
Anvith Thudi, Ilia Shumailov, Franziska Boenisch, Nicolas Papernot
2022arXiv.org21 citations
Semantic Scholar
CDI: Copyrighted Data Identification in Diffusion Models
Jan Dubinski, Antoni Kowalczuk, Franziska Boenisch, Adam Dziedzic
2024Computer Vision and Pattern Recognition20 citations
Semantic Scholar
Privacy Attacks on Image AutoRegressive Models
Antoni Kowalczuk, Jan Dubinski, Franziska Boenisch, Adam Dziedzic
2025International Conference on Machine Learning17 citations
Semantic Scholar
Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders
Jan Dubinski, Stanisław Pawlak, Franziska Boenisch, Tomasz Trzci'nski +1 more
2023Neural Information Processing Systems12 citations Open access
Semantic Scholar
Unlocking Post-hoc Dataset Inference with Synthetic Data
Bihe Zhao, Pratyush Maini, Franziska Boenisch, Adam Dziedzic
2025International Conference on Machine Learning11 citations
Semantic Scholar
Localizing Memorization in SSL Vision Encoders
Wen-Hao Wang, Adam Dziedzic, Michael Backes, Franziska Boenisch
2024Neural Information Processing Systems11 citations
Semantic Scholar
Learning with Impartiality to Walk on the Pareto Frontier of Fairness, Privacy, and Utility
Mohammad Yaghini, Patty Liu, Franziska Boenisch, Nicolas Papernot
2023arXiv.org11 citations Open access
Semantic Scholar
Is Federated Learning a Practical PET Yet?
Franziska Boenisch, Adam Dziedzic, R. Schuster, A. Shamsabadi +2 more
2023arXiv.org10 citations Open access
Semantic Scholar
Personalized Differential Privacy for Ridge Regression
Krishna N Acharya, Franziska Boenisch, Rakshit Naidu, Juba Ziani
2024arXiv.org9 citations
Semantic Scholar
Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models
Bartlomiej Marek, Lorenzo Rossi, Vincent Hanke, Xun Wang +3 more
2026arXiv.org8 citations
Semantic Scholar
Radioactive Watermarks in Diffusion and Autoregressive Image Generative Models
Michel Meintz, Jan Dubinski, Franziska Boenisch, Adam Dziedzic
2025arXiv.org8 citations
Semantic Scholar
Augment then Smooth: Reconciling Differential Privacy with Certified Robustness
Jiapeng Wu, Atiyeh Ashari Ghomi, D. Glukhov, Jesse C. Cresswell +2 more
2023Trans. Mach. Learn. Res.8 citations Open access
Semantic Scholar
Precise Parameter Localization for Textual Generation in Diffusion Models
Lukasz Staniszewski, Bartosz Cywi'nski, Franziska Boenisch, Kamil Deja +1 more
2025International Conference on Learning Representations7 citations
Semantic Scholar
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks
Antoni Kowalczuk, Jan Dubinski, Atiyeh Ashari Ghomi, Yi Sui +5 more
2024arXiv.org7 citations
Semantic Scholar
Differentially Private Prototypes for Imbalanced Transfer Learning
Dariush Wahdany, Matthew Jagielski, Adam Dziedzic, Franziska Boenisch
2024AAAI Conference on Artificial Intelligence7 citations Open access
Semantic Scholar
Captured by Captions: On Memorization and its Mitigation in CLIP Models
Wen-Hao Wang, Adam Dziedzic, Grace C. Kim, Michael Backes +1 more
2025International Conference on Learning Representations6 citations
Semantic Scholar
BitMark: Watermarking Bitwise Autoregressive Image Generative Models
Louis Kerner, Michel Meintz, Bihe Zhao, Franziska Boenisch +1 more
2025Neural Information Processing Systems6 citations
Semantic Scholar
Regulation Games for Trustworthy Machine Learning
Mohammad Yaghini, Patty Liu, Franziska Boenisch, Nicolas Papernot
2024arXiv.org5 citations
Semantic Scholar
Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks
Marcin Podhajski, Jan Dubinski, Franziska Boenisch, Adam Dziedzic +2 more
2024European Conference on Artificial Intelligence5 citations
Semantic Scholar
Natural Identifiers for Privacy and Data Audits in Large Language Models
Lorenzo Rossi, Bartlomiej Marek, Franziska Boenisch, Adam Dziedzic
2026arXiv.org4 citations
Semantic Scholar
Finding Dori: Memorization in Text-to-Image Diffusion Models Is Less Local Than Assumed
Antoni Kowalczuk, Dominik Hintersdorf, Lukas Struppek, K. Kersting +2 more
2025arXiv.org4 citations
Semantic Scholar
Demystifying Foreground-Background Memorization in Diffusion Models
Jimmy Z. Di, Yiwei Lu, Yao-Liang Yu, Gautam Kamath +2 more
2025AAAI Conference on Artificial Intelligence4 citations
Semantic Scholar
Memorization in Graph Neural Networks
Adarsh Jamadandi, Jing Xu, Adam Dziedzic, Franziska Boenisch
2025Neural Information Processing Systems4 citations
Semantic Scholar
Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs
Xun Wang, Jing Xu, Franziska Boenisch, Michael Backes +2 more
2025International Conference on Machine Learning4 citations
Semantic Scholar
Personalized PATE: Differential Privacy for Machine Learning with Individual Privacy Guarantees
Christopher Mühl, Franziska Boenisch
2022arXiv.org4 citations
Semantic Scholar
Adversarial Attacks and Defenses on Graph-aware Large Language Models (LLMs)
I. E. Olatunji, Franziska Boenisch, Jing Xu, Adam Dziedzic
2025arXiv.org3 citations
Semantic Scholar
On Stealing Graph Neural Network Models
Marcin Podhajski, Jan Dubinski, Franziska Boenisch, Adam Dziedzic +2 more
2025AAAI Conference on Artificial Intelligence3 citations
Semantic Scholar
Open LLMs are Necessary for Private Adaptations and Outperform their Closed Alternatives
Vincent Hanke, Tom Blanchard, Franziska Boenisch, I. E. Olatunji +2 more
3 citations
Semantic Scholar
Data Provenance for Image Auto-Regressive Generation
Bihe Zhao, Louis Kerner, Michel Meintz, Tameem Bakr +2 more
2026arXiv.org2 citations
Semantic Scholar
ADAGE: Active Defenses Against GNN Extraction
Jing Xu, Franziska Boenisch, Adam Dziedzic
2025ACM Asia Conference on Computer and Communications Security2 citations Open access
Semantic Scholar
Localizing and Mitigating Memorization in Image Autoregressive Models
Aditya Kasliwal, Franziska Boenisch, Adam Dziedzic
2025arXiv.org2 citations
Semantic Scholar
From Differential Privacy to Bounds on Membership Inference: Less can be More
Anvith Thudi, Ilia Shumailov, Franziska Boenisch, Nicolas Papernot
2024Trans. Mach. Learn. Res.2 citations
Semantic Scholar
Dataset Usage Inference without Shadow Models or Held-out Data
Wojciech Lapacz, Stanisław Pawlak, Jan Dubinski, Franziska Boenisch +1 more
2026arXiv.org1 citations
Semantic Scholar
AgentProv: Auditing Agentic LLM API Providers via Tool-use Policy Probes
Xun Wang, Bihe Zhao, Michael Backes, Franziska Boenisch +1 more
20261 citations
Semantic Scholar
Implementing Adaptations for Vision AutoRegressive Model
K. Shaikh, Franziska Boenisch, Adam Dziedzic
2025arXiv.org1 citations
Semantic Scholar
MUC: Machine Unlearning for Contrastive Learning with Black-box Evaluation
Yi-Han Wang, Yiwei Lu, Guojun Zhang, Franziska Boenisch +3 more
2024Trans. Mach. Learn. Res.1 citations
Semantic Scholar
MGI: Member vs Generated Inference
Bihe Zhao, Michel Meintz, Juan-Gui Xu, Franziska Boenisch +1 more
2026arXiv.org0 citations
Semantic Scholar
Watermark Degradation Across Model Iterations
Michel Meintz, M. Shah, Bihe Zhao, Louis Kerner +2 more
2026Information Hiding and Multimedia Security Workshop0 citations Open access
Semantic Scholar
TabPATE: Differentially Private Tabular In-Context Learning Without Public Data
Dariush Wahdany, Matthew Jagielski, Jesse C. Cresswell, Adam Dziedzic +1 more
2026arXiv.org0 citations
Semantic Scholar

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