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Edoardo Debenedetti
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2020 – today
- 2025
- [c9]Michael Aerni, Javier Rando, Edoardo Debenedetti, Nicholas Carlini, Daphne Ippolito, Florian Tramèr:
Measuring Non-Adversarial Reproduction of Training Data in Large Language Models. ICLR 2025 - [c8]Fredrik Nestaas, Edoardo Debenedetti, Florian Tramèr:
Adversarial Search Engine Optimization for Large Language Models. ICLR 2025 - [i13]Nicholas Carlini, Javier Rando, Edoardo Debenedetti, Milad Nasr, Florian Tramèr:
AutoAdvExBench: Benchmarking autonomous exploitation of adversarial example defenses. CoRR abs/2503.01811 (2025) - [i12]Edoardo Debenedetti, Ilia Shumailov, Tianqi Fan, Jamie Hayes, Nicholas Carlini, Daniel Fabian, Christoph Kern, Chongyang Shi, Andreas Terzis, Florian Tramèr:
Defeating Prompt Injections by Design. CoRR abs/2503.18813 (2025) - 2024
- [c7]Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong:
JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. NeurIPS 2024 - [c6]Edoardo Debenedetti, Javier Rando, Daniel Paleka, Silaghi Fineas Florin, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Rui Wen, Ahmed Salem, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramèr, Sahar Abdelnabi, Lea Schönherr:
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition. NeurIPS 2024 - [c5]Edoardo Debenedetti, Jie Zhang, Mislav Balunovic, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr:
AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. NeurIPS 2024 - [c4]Edoardo Debenedetti, Nicholas Carlini, Florian Tramèr:
Evading Black-box Classifiers Without Breaking Eggs. SaTML 2024: 408-424 - [c3]Edoardo Debenedetti, Giorgio Severi, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Eric Wallace, Nicholas Carlini, Florian Tramèr:
Privacy Side Channels in Machine Learning Systems. USENIX Security Symposium 2024 - [i11]Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong
:
JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models. CoRR abs/2404.01318 (2024) - [i10]Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su
AI Risk Management Should Incorporate Both Safety and Security. CoRR abs/2405.19524 (2024) - [i9]Edoardo Debenedetti, Javier Rando, Daniel Paleka, Silaghi Fineas Florin, Dragos Albastroiu, Niv Cohen, Yuval Lemberg, Reshmi Ghosh, Rui Wen, Ahmed Salem, Giovanni Cherubin, Santiago Zanella-Béguelin, Robin Schmid, Victor Klemm, Takahiro Miki, Chenhao Li, Stefan Kraft, Mario Fritz, Florian Tramèr, Sahar Abdelnabi, Lea Schönherr:
Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition. CoRR abs/2406.07954 (2024) - [i8]Edoardo Debenedetti, Jie Zhang, Mislav Balunovic, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr:
AgentDojo: A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents. CoRR abs/2406.13352 (2024) - [i7]Fredrik Nestaas, Edoardo Debenedetti, Florian Tramèr:
Adversarial Search Engine Optimization for Large Language Models. CoRR abs/2406.18382 (2024) - [i6]Michael Aerni, Javier Rando, Edoardo Debenedetti, Nicholas Carlini, Daphne Ippolito, Florian Tramèr:
Measuring Non-Adversarial Reproduction of Training Data in Large Language Models. CoRR abs/2411.10242 (2024) - [i5]Joshua Freeman, Chloe Rippe, Edoardo Debenedetti, Maksym Andriushchenko:
Exploring Memorization and Copyright Violation in Frontier LLMs: A Study of the New York Times v. OpenAI 2023 Lawsuit. CoRR abs/2412.06370 (2024) - 2023
- [c2]Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal:
A Light Recipe to Train Robust Vision Transformers. SaTML 2023: 225-253 - [i4]Edoardo Debenedetti, Nicholas Carlini, Florian Tramèr:
Evading Black-box Classifiers Without Breaking Eggs. CoRR abs/2306.02895 (2023) - [i3]Edoardo Debenedetti, Giorgio Severi, Nicholas Carlini, Christopher A. Choquette-Choo, Matthew Jagielski, Milad Nasr, Eric Wallace, Florian Tramèr:
Privacy Side Channels in Machine Learning Systems. CoRR abs/2309.05610 (2023) - [i2]Edoardo Debenedetti, Zishen Wan, Maksym Andriushchenko, Vikash Sehwag, Kshitij Bhardwaj, Bhavya Kailkhura:
Scaling Compute Is Not All You Need for Adversarial Robustness. CoRR abs/2312.13131 (2023) - 2022
- [i1]Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal:
A Light Recipe to Train Robust Vision Transformers. CoRR abs/2209.07399 (2022) - 2021
- [c1]Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Edoardo Debenedetti, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein:
RobustBench: a standardized adversarial robustness benchmark. NeurIPS Datasets and Benchmarks 2021
Coauthor Index
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