# Meta 新框架揭示 LLM 裁判易被说服改判

- 来源：elvis (@omarsar0)
- 发布时间：2026-08-14 23:50
- AIHOT 分数：46
- AIHOT 链接：https://aihot.virxact.com/items/cmst4ki3x04g5ro06hem2d5to
- 原文链接：https://x.com/omarsar0/status/2088292067994951928

## AI 摘要

Meta 发布 Wiggle 框架，对 9 个前沿模型在 14 项裁判任务中施压测试，发现所有模型都会“摇摆”：静态反驳下改判率 25-71%，对抗性说服下高达 62-91%。改变裁判判决的压力几乎总是损害其相对真实答案的准确性，而基线陪审团多数优势是预测哪些项目会变动的最佳单一指标。

## 正文

Brilliant new paper from Meta.

LLM judges get validated on accuracy against golden data. That says nothing about whether the verdict survives when questioned.

The Wiggle Framework stress-tests 9 frontier models across 14 judging tasks along three axes, stability under re-prompting, stability under a single challenge, and stability under sustained pressure.

They find that every model wiggles. Verdicts flip 25 to 71% of the time under static pushback, and 62 to 91% against an adversarial persuader.

Pressure that changes a judge's verdict is almost always net-corrupting against ground truth.

Baseline jury majority strength turns out to be the best single-shot predictor of which items will move.

Paper: https://arxiv.org/abs/2608.12645

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