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Rohan Paul· @rohanpaul_ai · X·· 2 小时前AI 评分54
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Google 论文《Thinking-in-Bets at Test Time Reduces Sycophantic Revisions in LLM Agents》提出一种免训练方法:Agent 在读取用户反馈前先私下记录主要论断、依据和置信度,被质疑时只复核有争议的部分。

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New Google paper finds that Gemini AI agents are much less likely to undo correct work after a user wrongly says “that’s wrong” if they first write down what they checked and how sure they are.

When a user says "that's wrong, redo it", agents often rewrite code that already passed its tests. Telling them to stand firm backfires, because they then ignore real bugs.

Thinking-in-Bets has the agent privately note its main claims, the checks behind them, and its confidence before seeing the reply. When challenged, it re-checks only the disputed claims and asks which case failed if the complaint is vague.

In patch review across 5 Gemini models, agents wrongly gave up 12.2% of correct requirements after a bare complaint, against 0.02% with the checklist. On report reviews, writing the checklist after the complaint reached only a 65% pass rate, against 89% when written first.

Agents that take user feedback should log what they verified, and how sure they are, before reading the reply.

– arxiv. org/abs/2610.34654

Title: "Thinking-in-Bets at Test Time Reduces Sycophantic Revisions in LLM Agents"

来源:Rohan Paul · x.com