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Current LLM agents struggle to keep pace with the complexities of real-life assistance, scoring low on a benchmark designed to test their proactive and persistent capabilities.
LLMs still fail at realistic search, with even the best models achieving only 30% F1 on a new benchmark designed to mimic the messy, multi-turn, and vaguely-defined search tasks that real users face.
