Edoardo Debenedetti

According to our database, Edoardo Debenedetti authored at least 10 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Adversarial Search Engine Optimization for Large Language Models.

Fredrik Nestaas, Edoardo Debenedetti, Florian Tramèr

CoRR, 2024

AgentDojo: A Dynamic Environment to Evaluate Attacks and Defenses for LLM Agents.

Edoardo Debenedetti, Jie Zhang, Mislav Balunovic, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr

CoRR, 2024

Dataset and Lessons Learned from the 2024 SaTML LLM Capture-the-Flag Competition.

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

CoRR, 2024

AI Risk Management Should Incorporate Both Safety and Security.

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, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal

CoRR, 2024

JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models.

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

CoRR, 2024

Privacy Side Channels in Machine Learning Systems.

Edoardo Debenedetti, Giorgio Severi, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Eric Wallace, Nicholas Carlini, Florian Tramèr

Proceedings of the 33rd USENIX Security Symposium, 2024

Evading Black-box Classifiers Without Breaking Eggs.

Edoardo Debenedetti, Nicholas Carlini, Florian Tramèr

Proceedings of the IEEE Conference on Secure and Trustworthy Machine Learning, 2024

2023

Scaling Compute Is Not All You Need for Adversarial Robustness.

Edoardo Debenedetti, Zishen Wan, Maksym Andriushchenko, Vikash Sehwag, Kshitij Bhardwaj, Bhavya Kailkhura

CoRR, 2023

A Light Recipe to Train Robust Vision Transformers.

Edoardo Debenedetti, Vikash Sehwag, Prateek Mittal

Proceedings of the 2023 IEEE Conference on Secure and Trustworthy Machine Learning, 2023

2021

RobustBench: a standardized adversarial robustness benchmark.

Francesco Croce, Maksym Andriushchenko, Vikash Sehwag, Edoardo Debenedetti, Nicolas Flammarion, Mung Chiang, Prateek Mittal, Matthias Hein

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021