Diagnosing Search Behavior and Failure Modes in Long-Horizon Search Agents

Deep search agents answer difficult information-seeking questions by iteratively issuing search queries to gather supporting evidence, but it remains unclear whether and how greater search effort leads to better answers. We study these questions through a trajectory-level diagnosis of long-horizon search agents. Using human-annotated document-level relevance judgments, we evaluate the evidence retrieved at each search step and separate two stages of agent behavior: what evidence an agent retriev

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ethics.ai (3 August 2026), “Diagnosing Search Behavior and Failure Modes in Long-Horizon Search Agents,” evidence record 15891, https://ethics.ai/record/15891 (originally published by arXiv).

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