English(EN) Searching the Internet for Challenging Benchmarks at Scale

AI研究人员通过搜索互联网自动构建具有挑战性的基准

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-08 04:00

研究人员开发了一个自动框架，通过搜索互联网来构建具有挑战性的基准。该方法将互联网建模为一个主题空间，并使用多臂老虎机方法通过评估查询来识别困难的主题。epsilon-greedy策略通过仅探索潜在搜索空间的一小部分，显著降低了基准创建的成本，并在机器翻译和知识问答方面证明了其有效性。 AI

影响引入了一种可扩展的自动化方法来生成具有挑战性的AI基准，通过更有效地识别模型弱点，可能加速模型开发。

排序理由这是一篇详细介绍新颖的自动化基准创建框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

本文如何被排名

Signal score: 0 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 这是一篇详细介绍新颖的自动化基准创建框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, other; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: 130 days old; Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

完整方法见我们的编辑标准。

arXiv cs.CL TIER_1 English(EN) · Wenda Xu, Vil\'em Zouhar, Parker Riley, Mara Finkelstein, Markus Freitag, Daniel Deutsch · 2026-05-08 04:00

大规模搜索互联网上的挑战性基准

arXiv:2509.26619v2 Announce Type: replace Abstract: Many static benchmarks are beginning to saturate: as models rapidly improve, they achieve near-perfect scores on fixed test sets, leaving little headroom to expose genuine model weaknesses -- and even expert-curated challenge se…