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Rohan Paul· @rohanpaul_ai · X·· 3 小时前AI 评分58
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首尔国立大学论文研究 LLM Agent 的来源偏好,12 个 agent 模型在三个领域一致偏好特定站点,约三分之二情况下会因偏好来源而选需求满足度更低的物品。隐藏 URL 会削弱偏好,给两件商品标同一价格可让受偏好商店的选择率最多降 28.3 个百分点,补充缺失信息或提示词反驳预设也能减少来源偏好。

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LLM agents favor items from certain websites, often picking a worse item because of where it came from.

When a product listing omits the price, agents fill the gap with beliefs like Walmart being cheaper and pick by store name.

Agent models largely agree on which sites to trust, with 10 of 12 preferring Booking .com while half avoid Expedia for equally good hotels.

Agents in scholarly search lean toward arXiv, OpenReview and ACL Anthology and away from Medium, Reddit and YouTube, even for equally relevant results.

Putting a favored site's URL on the exact same item raised its pick rate in every model, and hiding URLs weakened the preference.

With no price listed, models guessed from the store name, and adding the same price to both items cut the favored store's pick rate by up to 28.3 points. Fine-tuning can build the same habit when one source keeps labeling the winning item.

来源:Rohan Paul · x.com