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Keenable AI open-sources NEEDLE, a dynamic web search benchmark

By PulseAugur Editorial · [1 sources] ·

Keenable AI has open-sourced NEEDLE, a new benchmark designed to evaluate web search APIs by dynamically generating query sets hourly and daily. This approach prevents agents from accessing pre-existing answers, ensuring a more accurate assessment of their retrieval capabilities. NEEDLE categorizes queries into News, Finance, Scholar, Deep-tail, and Legal, with scoring methods tailored to each vertical. The benchmark also establishes an 'ultimate ceiling' by pooling results from all tested search APIs, allowing for a clear distinction between ranking issues and market-wide retrieval problems. AI

IMPACT Provides a more robust method for evaluating search agents, potentially driving improvements in retrieval and ranking quality across the industry.

RANK_REASON Open-source release of a new benchmark for evaluating AI search capabilities. [lever_c_demoted from research: ic=1 ai=1.0]

Read on MarkTechPost →

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

Keenable AI open-sources NEEDLE, a dynamic web search benchmark

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43 / 100
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Open-source release of a new benchmark for evaluating AI search capabilities. [lever_c_demoted from research: ic=1 ai=1.0]
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. MarkTechPost TIER_1 English(EN) · Asif Razzaq ·

    Keenable AI Open-Sources NEEDLE: A Live Search Benchmark That Rebuilds Its Query Set Every Hour

    <p>How do you benchmark a web search API when the thing being tested can read the answer key? A search agent has a fetch tool. If the gold labels sit in a public dataset, the agent can download them mid-evaluation and skip retrieval entirely. A similar problem arises when the ans…

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