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Who is the Agent to Blame? Localizing Faithfulness and Citation Mistakes in Agentic Deep Research

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

Deep research (DR) systems produce long-form cited reports by orchestrating multiple agents that search and synthesize information from the web. Citations are the primary mechanism for evaluating the faithfulness of these reports, yet current DR systems exhibit poor citation recall. Moreover, improving citation recall is challenging because DR systems are complex multi-agent architectures where information passes through agents like a telephone game, and both content and citations can get corrupted along the way. We propose an evaluation method that pinpoints which agent introduced each error

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Evidence & attribution

First collected: 2026-09-21T10:02:02.728Z. This is not the publication date.