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New benchmark evaluates AI agent search value

Researchers have introduced SearchHorizonBench, a new benchmark designed to evaluate how well AI agents can determine the value of conducting additional searches. The benchmark aims to improve decision-making by estimating the potential benefit of a search relative to its cost, moving beyond simple question difficulty. It includes 45,632 executions across 3,168 questions, with a focus on reducing Brier error and understanding the variance in search gains. AI

IMPACT This benchmark could lead to more efficient and cost-effective AI agents by improving their ability to assess the value of information retrieval.

RANK_REASON The cluster describes a new benchmark for AI research published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

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

New benchmark evaluates AI agent search value

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The cluster describes a new benchmark for AI research published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Jingjie Ning, Xueqi Li, Yibo Kong ·

    SearchHorizonBench: A Benchmark for Search Value in AI Agents

    arXiv:2610.34714v1 Announce Type: new Abstract: AI agents must decide when another search is worth its cost. Answer-success probabilities capture question difficulty, while this decision requires estimating the additional benefit of search. We introduce SearchHorizonBench, a benc…