The Agent's First Day: Benchmarking Learning, Exploration, and Scheduling in the Workplace Scenarios 事件

The Agent's First Day: Benchmarking Learning, Exploration, and Scheduling in the Workplace Scenarios arXiv:2601.08173v2 Announce Type: replace Abstract: The rapid evolution of Multi-modal Large Language Models (MLLMs) has advanced workflow automation; however, existing research mainly targets performance upper bounds in static environments, overlooking robustness for stochastic real-world deployment. We identify three key challenges: dynamic task scheduling, active exploration under uncertainty