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Rohan Paul· @rohanpaul_ai · X·· 2 小时前AI 评分52
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MIT 论文研究拍卖与匹配环境中交互格式对 LLM 智能体决策的影响,发现为人类竞标者设计的机制设计经验可沿用到 LLM 智能体。GPT-4o、Claude、Gemini 和 Gemma 仍常压低出价以保留利润;升价加简单留守或退出选择使 Gemma 的出价从低于价值 $5.30 收窄到 $0.30,一行说明拒绝只会重新分配的提示把匹配错误从 4.2% 降到 0.2%。

正文

New MIT Paper: LLM agents decide better when the choice is shown in simple steps or the rule's safe move is stated plainly, and worse when told to reason about opponents.

Market-design rules of thumb built for human bidders carry over to LLM agents, so we can borrow them instead of inventing new prompt tricks.

Honest bids and rankings are always the best move in these auctions and matching games. GPT-4o, Claude, Gemini and Gemma still underbid, often to keep a profit margin.

A rising price with a simple stay-or-exit choice moved Gemma from $5.30 below its value to $0.30 below. A 1-line note that rejections only redirect cut matching errors from 4.2% to 0.2%.

Fix the format and state the key fact before adding reasoning prompts, and judge agents by their choices, since their written plans missed these gains.

Agent prompts should state facts about the rules rather than request more thinking, because facts improved choices while thinking prompts often added errors.

来源:Rohan Paul · x.com