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AI 味检测器 Slop Meter 与 Jev 的正面对比

同一批 600 段文本、176 项特征下,Jev 几乎全答但错 193 条,Slop Meter 只答九分之一且仅错一条,作者借此说明「敢说不知道」的价值。

Zaid
@zaidmukaddam2026.09.23收录原推发布于 2026.09.22
AI 味检测器 Slop Meter 与 Jev 的正面对比(第 1 张,共 4 张)
AI 味检测器 Slop Meter 与 Jev 的正面对比(第 2 张,共 4 张)
AI 味检测器 Slop Meter 与 Jev 的正面对比(第 3 张,共 4 张)
AI 味检测器 Slop Meter 与 Jev 的正面对比(第 4 张,共 4 张)
Zaid @zaidmukaddam原推发布于 2026.09.22
在 X 上打开原推

I built an AI slop detector that mostly shuts up. Every detector I tried had an answer for every paragraph, and I think that is the bug. A tool that calls 15% of human writing "AI" is not detecting much of anything. It's accusing people. Slop Meter says can't tell on 87% of paragraphs and is right 97.4% of the time when it does speak. On 24,000 human-written web pages it flagged 0.31%. Same 600 test paragraphs, head to head with Jev, @typesafeai's calibrated decision model, given the same 176 measurements: Jev answered nearly all of them and got 193 wrong. Slop Meter answered 1 in 9 and got a single one wrong. How: no LLM in the default path. A 56 KB MLP over 176 stylometric features (38 rulebook tells, function-word rates, sentence rhythm). Opt-in Sharper mode adds SmolLM2-135M in your browser on WebGPU, 8 Binoculars/DetectGPT-style features, 3 networks merged into one. All on-device, text never leaves. http://slop-meter.com

x.com/zaidmukaddam/status/2102359784217530845采集于 2026.09.23 10:17