
Teaching Agents When to Ask for Context
This paper frames context acquisition as active inference, enabling agents to choose among clarifying questions, retrieval, tool calls, task actions, or stopping. It introduces an Optimal Question Asking benchmark and evaluates language models on tasks involving 25 to 300 candidates, as well as clarification before generation and prompt optimization.






