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ParanoiaEval is introduced as the first benchmark to systematically evaluate risk-treatment behaviors in autonomous coding agents. It unifies existing fragmented evaluation methods to better assess whether agents' defensive actions are warranted.
ParanoiaEval is introduced as the first benchmark to systematically evaluate risk-treatment behaviors in autonomous coding agents. It unifies existing fragmented evaluation methods to better assess whether agents' defensive actions are warranted.
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As coding agents increasingly undertake real-world work autonomously, judging whether their risk treatments are warranted has become important. Existing work evaluates related agent behaviors from separate perspectives, but lacks a systematic framework for unifying these behaviors. To bridge this gap, we introduce...
As coding agents take on more real-world tasks autonomously, understanding and judging their risk management is critical to ensure efficiency and reliability. ParanoiaEval provides a standardized framework to measure unnecessary defensive work, helping improve agent performance.
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