| Differentially private fine-tuning of language models D Yu, S Naik, A Backurs, S Gopi, HA Inan, G Kamath, J Kulkarni, YT Lee, ... arXiv preprint arXiv:2110.06500, 2021 | 535 | 2021 |
| Analyzing leakage of personally identifiable information in language models N Lukas, A Salem, R Sim, S Tople, L Wutschitz, S Zanella-Béguelin 2023 IEEE Symposium on Security and Privacy (SP), 346-363, 2023 | 384 | 2023 |
| Numerical composition of differential privacy S Gopi, YT Lee, L Wutschitz Advances in Neural Information Processing Systems 34, 11631-11642, 2021 | 240 | 2021 |
| Analyzing information leakage of updates to natural language models S Zanella-Béguelin, L Wutschitz, S Tople, V Rühle, A Paverd, ... Proceedings of the 2020 ACM SIGSAC conference on computer and communications …, 2020 | 171 | 2020 |
| Bayesian estimation of differential privacy S Zanella-Beguelin, L Wutschitz, S Tople, A Salem, V Rühle, A Paverd, ... International Conference on Machine Learning, 40624-40636, 2023 | 72 | 2023 |
| Training data leakage analysis in language models HA Inan, O Ramadan, L Wutschitz, D Jones, V Rühle, J Withers, R Sim arXiv preprint arXiv:2101.05405, 2021 | 66 | 2021 |
| Differentially private model compression F Mireshghallah, A Backurs, HA Inan, L Wutschitz, J Kulkarni Advances in Neural Information Processing Systems 35, 29468-29483, 2022 | 28 | 2022 |
| Securing AI Agents with Information-Flow Control M Costa, B Köpf, A Kolluri, A Paverd, M Russinovich, A Salem, S Tople, ... arXiv preprint arXiv:2505.23643, 2025 | 22 | 2025 |
| dp-transformers: Training transformer models with differential privacy L Wutschitz, HA Inan, A Manoel | 22 | 2022 |
| Rethinking privacy in machine learning pipelines from an information flow control perspective L Wutschitz, B Köpf, A Paverd, S Rajmohan, A Salem, S Tople, ... arXiv preprint arXiv:2311.15792, 2023 | 16 | 2023 |
| Contextual integrity in llms via reasoning and reinforcement learning G Lan, HA Inan, S Abdelnabi, J Kulkarni, L Wutschitz, R Shokri, ... arXiv preprint arXiv:2506.04245, 2025 | 15 | 2025 |
| A full-field simulation methodology for sonic boom modeling on adaptive Cartesian cut-cell meshes R Yamashita, L Wutschitz, N Nikiforakis Journal of Computational Physics 408, 109271, 2020 | 15 | 2020 |
| Privacy analysis in language models via training data leakage report HA Inan, O Ramadan, L Wutschitz, D Jones, V Rühle, J Withers, R Sim ArXiv, abs/2101.05405, 2021 | 13 | 2021 |
| {Closed-Form} bounds for {DP-SGD} against record-level inference attacks G Cherubin, B Köpf, A Paverd, S Tople, L Wutschitz, S Zanella-Béguelin 33rd USENIX Security Symposium (USENIX Security 24), 4819-4836, 2024 | 12 | 2024 |
| Permissive Information-Flow Analysis for Large Language Models SA Siddiqui, R Gaonkar, B Köpf, D Krueger, A Paverd, A Salem, S Tople, ... arXiv preprint arXiv:2410.03055, 2024 | 9 | 2024 |
| The Canary's Echo: Auditing Privacy Risks of LLM-Generated Synthetic Text M Meeus, L Wutschitz, S Zanella-Béguelin, S Tople, R Shokri arXiv preprint arXiv:2502.14921, 2025 | 7 | 2025 |
| Acon: Optimizing context compression for long-horizon llm agents M Kang, WN Chen, D Han, HA Inan, L Wutschitz, Y Chen, R Sim, ... arXiv preprint arXiv:2510.00615, 2025 | 6 | 2025 |
| Simulating environments with reasoning models for agent training Y Li, HA Inan, X Yue, WN Chen, L Wutschitz, J Kulkarni, R Poovendran, ... arXiv preprint arXiv:2511.01824, 2025 | 2 | 2025 |
| Learning gui grounding with spatial reasoning from visual feedback Y Zhao, WN Chen, HA Inan, S Kessler, L Wang, L Wutschitz, F Yang, ... arXiv preprint arXiv:2509.21552, 2025 | 2 | 2025 |
| Quantifying machine-learning model resilience against inference attacks G Cherubin, BA KÖPF, AJ PAVERD, SS TOPLE, L WUTSCHITZ, ... US Patent App. 18/400,422, 2025 | 1 | 2025 |
