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swyx· @swyx · X·· 1 天前AI 评分30
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swyx 在录制 AAv5 播客时提出,不能信任实验室不刻意或无意地 benchmaxx,需要可信第三方按原意重做整套评测。他以随机打乱选择题顺序、换用表面不同但考察同一推理步骤的新题等微扰方式,检验模型宣称是否成立,并称系统性识别 benchmaxx 的办法就是为每个评测都建 altbench。

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we're recording an AAv5 pod with @_micah_h and @grmcameron today and this reminds me why you basically need @ArtificialAnlys AA-* rebuilds of every single eval

because you -CANNOT- trust labs not to intentionally or accidentally benchmaxx, you need a few trusted third parties to basically redo the entire eval in spirit but not in letter, to have a quick sniff test that model claims hold up under minor perturbations (eg starting from "randomizing order in multiple choice questions" to coming up with completely new problems that superficially look different but actually test the same underlying logic and reasoning steps). not enough people are reading bench traces like this 👇 and the systematic way to catch this benchmaxxing is basically to have altbenches for everything

引用Joachim Schaeffer@JSchaeff3r
Kimi K3.1 recalls instructions it was never given on Terminal Bench. They match the hidden tests. K3.1 while solving: "Instructions likely distilled pitfalls from previous agents." 🤯 When we edit a task to contradict them, K3.1 refuses the new instructions and fails. Other models follow the edit. Is it terminal(ly) benchmaxxed? 🧵
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来源:swyx · x.com