| Bayesian framework for gradient leakage M Balunović, DI Dimitrov, R Staab, M Vechev arXiv preprint arXiv:2111.04706, 2021 | 47 | 2021 |
| Beyond memorization: Violating privacy via inference with large language models R Staab, M Vero, M Balunović, M Vechev arXiv preprint arXiv:2310.07298, 2023 | 46 | 2023 |
| Effective certification of monotone deep equilibrium models MN Müller, R Staab, M Fischer, MT Vechev CoRR, abs/2110.08260, 2021 | 6 | 2021 |
| Watermark stealing in large language models N Jovanović, R Staab, M Vechev arXiv preprint arXiv:2402.19361, 2024 | 5 | 2024 |
| Abstract interpretation of fixpoint iterators with applications to neural networks MN Müller, M Fischer, R Staab, M Vechev Proceedings of the ACM on Programming Languages 7 (PLDI), 786-810, 2023 | 4 | 2023 |
| Large language models are advanced anonymizers R Staab, M Vero, M Balunović, M Vechev arXiv preprint arXiv:2402.13846, 2024 | 3 | 2024 |
| Private Attribute Inference from Images with Vision-Language Models B Tömekçe, M Vero, R Staab, M Vechev arXiv preprint arXiv:2404.10618, 2024 | 1 | 2024 |
| From Principle to Practice: Vertical Data Minimization for Machine Learning R Staab, N Jovanović, M Balunović, M Vechev arXiv preprint arXiv:2311.10500, 2023 | 1 | 2023 |
| A Synthetic Dataset for Personal Attribute Inference H Yukhymenko, R Staab, M Vero, M Vechev arXiv preprint arXiv:2406.07217, 2024 | | 2024 |
| Exploiting LLM Quantization K Egashira, M Vero, R Staab, J He, M Vechev arXiv preprint arXiv:2405.18137, 2024 | | 2024 |
| Back to the Drawing Board for Fair Representation Learning A Pouget, N Jovanović, M Vero, R Staab, M Vechev arXiv preprint arXiv:2405.18161, 2024 | | 2024 |
| Black-Box Detection of Language Model Watermarks T Gloaguen, N Jovanovic, R Staab, M Vechev | | |
| Large Language Models are Anonymizers R Staab, M Vero, M Balunovic, M Vechev ICLR 2024 Workshop on Reliable and Responsible Foundation Models, 0 | | |
