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New benchmark reveals AI struggles to combine web search and database data

By PulseAugur Editorial · [1 sources] ·

A new benchmark called HybridDeepResearch has been introduced to evaluate AI agents' ability to combine information from both web searches and structured database queries. This benchmark, containing 380 tasks, aims to address the limitation of existing evaluations that assess these modalities in isolation. Initial results show that even advanced models like GLM-5.2, Claude Sonnet 4.6, and GPT-5 achieve only around 50-54% success on challenging tasks, indicating that effectively bridging structured and unstructured data remains a significant hurdle for AI agents. AI

IMPACT Highlights a key challenge in AI agent development: integrating diverse data sources effectively.

RANK_REASON The cluster contains a research paper introducing a new benchmark for AI agents. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New benchmark reveals AI struggles to combine web search and database data

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The cluster contains a research paper introducing a new benchmark for AI agents. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Ruofan Wu, Peiran Xu, Xiaolong Li, Fan Shu, Soyoung Yoon, Yite Wang, Xiaodong Yu, Boyi Liu, Feng Yan, Debiao Li, Yuxiong He, Zhewei Yao ·

    Benchmarking Hybrid Deep Research Across Database Querying and Web Search

    arXiv:2609.09410v1 Announce Type: new Abstract: While autonomous agents have made significant strides in "deep research" by iteratively navigating the open web to synthesize information, real-world problem-solving is rarely confined to a single environment. Complex analytical tas…

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