English(EN) Jointly Modeling Preferences and Imperfect Decision-Making in Large Language Models

新模型联合预测大型语言模型的偏好和不完美决策

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 04:00

研究人员开发了一个名为偏好-行为模型（PBM）的新框架，以更好地理解大型语言模型（LLM）在复杂场景下如何做出决策。该模型结合了LLM的明确偏好和解释不完美效用最大化的机制，从而可以从观察到的选择中联合推断偏好和行为参数。在公共物品博弈和集体风险困境等社会困境中的实验表明，虽然标准的征询工具未能持续预测LLM的行为，但PBM在不同困境中均显示出预测价值。PBM还揭示，LLM的偏好通常与角色指令一致，但在不同维度、模型和特定博弈中可能存在分歧。 AI

影响为理解和对齐LLM在复杂、多目标场景下的决策提供了框架。

排序理由介绍LLM行为新建模框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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本文如何被排名

Signal score: 9 / 100; Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket: Tool; 介绍LLM行为新建模框架的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
Source corroboration: Single-source cluster; Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics: paper, model release; Editorial topic classification. Feeds into how the story surfaces on /topic/<slug> hub pages and into the per-entity coverage mix.
AI-industry relevance: High; Clearly on-topic for AI-industry coverage.
Story freshness: Same-day; Cluster formed today. Ranking reflects the current source set at time of score.

完整方法见我们的编辑标准。

报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Axel Abels, Elias Fern\'andez Domingos, Tom Lenaerts · 2026-10-27 04:00

联合建模大型语言模型中的偏好和不完美决策

arXiv:2610.33651v1 Announce Type: new Abstract: Do preferences Large Language Models (LLMs) express in standard elicitation tasks predict their strategic behaviour? LLM agents interacting with humans and other AI systems face potentially conflicting objectives, such as individual…

本文如何被排名

报道来源 [1]

联合建模大型语言模型中的偏好和不完美决策

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