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This paper studies the effect of retrieval-augmented generation in single-turn mental-health question answering and introduces a selective retrieval policy to balance response specificity and safety.
Introduces Agent Retrieval Bench, a file-level benchmark evaluating how well coding agents retrieve relevant repository files during the context-acquisition stage. The benchmark includes 427 samples across 25 repositories and evaluates various retrieval methods, finding no single family dominates.