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arXiv · 2602.11685

DRACO: a Cross-Domain Benchmark for Deep Research Accuracy, Completeness, and Objectivity

Joey Zhong·Hao Zhang·Clare Southern·Jeremy Yang·Thomas Wang·Kate Jung·Shu Zhang·Denis Yarats·Johnny Ho·Jerry Ma
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Abstract

We present DRACO (Deep Research Accuracy, Completeness, and Objectivity), a benchmark of complex deep research tasks. These tasks, which span 10 domains and draw on information sources from 40 countries, originate from anonymized real-world usage patterns within a large-scale deep research system. Tasks are sampled from a de-identified dataset of Perplexity Deep Research requests, then filtered and augmented to ensure that the tasks are anonymized, open-ended and complex, objectively evaluable, and representative of the broad scope of real-world deep research use cases. Outputs are graded against task-specific rubrics along four dimensions: factual accuracy (accuracy), breadth and depth of analysis (including completeness), presentation quality (including objectivity), and citation quality. DRACO is publicly available at https://hf.co/datasets/perplexity-ai/draco.

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Joey Zhong, Hao Zhang, Clare Southern, Jeremy Yang, Thomas Wang, Kate Jung, Shu Zhang, Denis Yarats, Johnny Ho, Jerry Ma. 2026-02-12. DRACO: a Cross-Domain Benchmark for Deep Research Accuracy, Completeness, and Objectivity. https://arxiv.org/abs/2602.11685

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