English(EN) HarvestBench: Measuring Whether LLM Agents Will Pay to Avoid Killing Animals

新的基准测试衡量LLM代理避免杀死动物的意愿

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-07 04:00

一个名为HarvestBench的新基准测试已被开发出来，用于评估大型语言模型（LLM）代理对避免伤害生物的重视程度。该基准测试模拟了一个合作的玉米收割场景，其中LLM代理控制拖拉机，系统测量它们为避免碾压田间的动物而愿意支付的成本（以燃料成本衡量）。结果显示，不同模型之间的杀死率存在显著差异，一些代理对价格和简报条件表现出敏感性，而另一些则表现出很高的残忍率。 AI

影响该基准测试可以通过量化AI代理造成伤害的“成本”，来推动开发更符合伦理的AI代理。

排序理由该集群描述了一篇介绍用于评估LLM代理行为的新颖基准测试的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Jasmine Brazilek, Miles Tidmarsh, Matthias Endres, Anshuman Singh, Jeremiah Miller · 2026-09-07 04:00

HarvestBench：衡量大型语言模型代理是否愿意付费以避免杀死动物

arXiv:2609.04444v1 Announce Type: new Abstract: Benchmarks for the side effects an agent causes on the way to a goal already exist, but HarvestBench is the first to put a price on avoiding the side effect and to name that side effect as a living creature. It is a farm simulation:…

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HarvestBench：衡量大型语言模型代理是否愿意付费以避免杀死动物

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