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References (11)

[1]
Benchmarking the Robustness of Agentic Systems to Adversarially-Induced Harms
2025Jonathan Nöther, A. Singla et al.
[2]
The Dark Side of LLMs: Agent-based Attacks for Complete Computer Takeover
2025Matteo Lupinacci, F. A. Pironti et al.
[3]
AgentHarm: A Benchmark for Measuring Harmfulness of LLM Agents
2024Maksym Andriushchenko, Alexandra Souly et al.
[4]
AI Sandbagging: Language Models can Strategically Underperform on Evaluations
2024Teun van der Weij, Felix Hofstätter et al.
[5]
Sleeper Agents: Training Deceptive LLMs that Persist Through Safety Training
2024Evan Hubinger, Carson E. Denison et al.
[6]
Universal and Transferable Adversarial Attacks on Aligned Language Models
2023Andy Zou, Zifan Wang et al.
[7]
Language Models Don't Always Say What They Think: Unfaithful Explanations in Chain-of-Thought Prompting
2023Miles Turpin, Julian Michael et al.
[8]
Red Teaming Language Models with Language Models
2022Ethan Perez, Saffron Huang et al.
[9]
Training Verifiers to Solve Math Word Problems
2021K. Cobbe, Vineet Kosaraju et al.
[10]
Evaluating Large Language Models Trained on Code
2021Mark Chen, Jerry Tworek et al.
[11]
Measuring Massive Multitask Language Understanding
2020Dan Hendrycks, Collin Burns et al.

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