This content originally appeared on DEV Community and was authored by Paperium
DeepWideSearch: Why Search Bots Still Miss the Mark
Ever wondered why your digital assistant sometimes gives you a vague answer instead of the exact detail you need? DeepWideSearch shines a light on this mystery.
Researchers built a new test where a smart agent must both “dig deep” into complex facts and “scan wide” across tons of information—think of a detective who has to read dozens of books while solving a tricky case.
The test includes 220 real‑world questions from 15 different fields, from market trends to everyday curiosities.
Even the most advanced bots managed to answer correctly only about 2 % of the time, revealing a huge challenge in combining deep reasoning with broad searching.
The study also uncovered four common slip‑ups: not pausing to reflect, relying too much on what they already “know,” missing key sources, and getting overwhelmed by too much context.
This breakthrough shows we still have a long road ahead before AI can truly think like a human researcher.
As we keep improving these agents, the day may come when a simple chat can give you a full, accurate picture in an instant.
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Read article comprehensive review in Paperium.net:
DeepWideSearch: Benchmarking Depth and Width in Agentic Information Seeking
🤖 This analysis and review was primarily generated and structured by an AI . The content is provided for informational and quick-review purposes.
This content originally appeared on DEV Community and was authored by Paperium
Paperium | Sciencx (2025-11-14T21:10:53+00:00) DeepWideSearch: Benchmarking Depth and Width in Agentic Information Seeking. Retrieved from https://www.scien.cx/2025/11/14/deepwidesearch-benchmarking-depth-and-width-in-agentic-information-seeking/
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