VQV Signal
AgentTime is a new benchmark designed to evaluate AI agents' ability to estimate and control their own runtime, focusing on duration-following and time-awareness. This addresses a gap in prior research that has not explored native agent runtime control.
AgentTime is a new benchmark designed to evaluate AI agents' ability to estimate and control their own runtime, focusing on duration-following and time-awareness. This addresses a gap in prior research that has not explored native agent runtime control.
AI-assisted summary based on the listed source.
An essential control of AI agents is their ability to manage runtime. This ability requires a sense of time-awareness, to predict and estimate wall-clock time and to control their own actions. Prior work has focused on time-awareness, but duration-following and control in native agent harnesses remain unexplored....
Effective runtime management is crucial for AI agents to perform tasks within specified time constraints, enhancing their reliability and autonomy. AgentTime provides a standardized way to measure and improve these capabilities.
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VQV surfaced this signal because it is recent, relevant to AI Agents, connected to arXiv.
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