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It is found that agents are less effective at resolving tasks when building on agent code compared to human code, with task resolve rate drops of up to 13.1%.
AppWorld-UL is introduced, a ``user-in-the-loop''benchmark of 516 challenging tasks requiring diverse agent-user interactions that systematically modify original tasks to introduce ambiguities and constraints that necessitate various types of agent-user interaction.
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