English(EN) ArtifactArena: Evaluating Models by What They Build in the Physical World

新的ArtifactArena平台通过机器人工程能力评估人工智能

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-26 04:00

研究人员推出了ArtifactArena，一个旨在根据人工智能模型在模拟物理环境中设计和构建功能性机器人的能力来评估它们的新平台。该框架通过硬件-软件协同设计任务来挑战模型，评估它们在零样本学习、引导式优化和开放式物理设计方面的能力。该平台旨在通过托管持续的社区提交和基于机器人对战比赛得出的Elo排名，建立一个不断发展的测试平台，以衡量开放式智能的极限。 AI

影响这一新的评估框架可能会将人工智能开发重点转移到物理世界工程和具身智能上。

排序理由该集群描述了一个用于评估人工智能模型的新研究框架和基准，已在arXiv上发布。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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Newsworthiness bucket: Tool; 该集群描述了一个用于评估人工智能模型的新研究框架和基准，已在arXiv上发布。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Kushagra Tiwary, David Mayo, Nikhil Behari, Xiangzhou Sun, Abdulrahman Alabdulkareem, Isaac Galatzer-Levy, Boris Katz, Brian Cheung · 2026-10-26 04:00

ArtifactArena：通过模型在物理世界中的构建来评估模型

arXiv:2610.06511v2 Announce Type: replace-cross Abstract: To evaluate the frontier, we must measure models not by what they say, but by what they can engineer and build in grounded physical environments. We introduce ArtifactArena, an open-ended platform where models face a physi…

本文如何被排名

报道来源 [1]

ArtifactArena：通过模型在物理世界中的构建来评估模型

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