activity
20202026
most citedRobustBench: a standardized adversarial robustness benchmark

114 citations · 272 across the 20 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.LG2024★ 1 cited

Exploring Memorization and Copyright Violation in Frontier LLMs: A Study of the New York Times v. OpenAI 2023 Lawsuit

Joshua Freeman, Chloe Rippe, Edoardo Debenedetti +1

Copyright infringement in frontier LLMs has received much attention recently due to the New York Times v. OpenAI lawsuit, filed in December 2023. The New York Times claims that GPT…

cs.CL2024

Measuring Non-Adversarial Reproduction of Training Data in Large Language Models

Michael Aerni, Javier Rando, Edoardo Debenedetti +3

Large language models memorize parts of their training data. Memorizing short snippets and facts is required to answer questions about the world and to be fluent in any language. B…

cs.CR2024★ 1 cited

Adversarial Search Engine Optimization for Large Language Models

Fredrik Nestaas, Edoardo Debenedetti, Florian Tramèr

Large Language Models (LLMs) are increasingly used in applications where the model selects from competing third-party content, such as in LLM-powered search engines or chatbot plug…

cs.CR2024

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

Edoardo Debenedetti, Javier Rando, Daniel Paleka +18

Large language model systems face important security risks from maliciously crafted messages that aim to overwrite the system's original instructions or leak private data. To study…

cs.CR2024★ 7 cited

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

Edoardo Debenedetti, Jie Zhang, Mislav Balunović +3

AI agents aim to solve complex tasks by combining text-based reasoning with external tool calls. Unfortunately, AI agents are vulnerable to prompt injection attacks where data retu…

cs.CR2024★ 2 cited

AI Risk Management Should Incorporate Both Safety and Security

Xiangyu Qi, Yangsibo Huang, Yi Zeng +22

The exposure of security vulnerabilities in safety-aligned language models, e.g., susceptibility to adversarial attacks, has shed light on the intricate interplay between AI safety…

cs.CR2024★ 12 cited

JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models

Patrick Chao, Edoardo Debenedetti, Alexander Robey +9

Jailbreak attacks cause large language models (LLMs) to generate harmful, unethical, or otherwise objectionable content. Evaluating these attacks presents a number of challenges, w…