English(EN) Behavior2Trip: Towards Personalized Travel Planning via User Behavior Trajectory

新的Behavior2Trip基准挑战LLM在个性化旅行规划方面的能力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-28 04:00

研究人员推出了Behavior2Trip (B2T)，一个通过分析用户行为轨迹进行个性化旅行规划的新基准和智能体。与依赖明确指令的现有方法不同，B2T从过去的行动中推断偏好，减轻了用户的交互负担。该基准源自一个大型中文旅行平台，包含11,400个用户行为实例。实验表明，像GPT-4.1这样的当前大型语言模型在此任务上面临挑战，通过率较低，而提出的B2T-Agent，特别是基于Qwen3-8B构建时，则展现出卓越的性能和泛化能力。 AI

影响这项研究突显了从行为中推断用户偏好的挑战，有望在各个领域催生更复杂的个性化AI智能体。

排序理由该集群描述了一篇介绍新基准和针对特定AI任务的智能体的新学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Zihao Cheng, Yingyu Shan, Hongru Wang, Zeming Liu, Xinyi Wang, Xiangrong Zhu, Yuhang Guo, Wei Lin, Yunhong Wang · 2026-08-28 04:00

Behavior2Trip：通过用户行为轨迹实现个性化旅行规划

arXiv:2608.26807v1 Announce Type: cross Abstract: Travel planning agents assist users in generating personalized travel plans by modeling their individual preferences. Existing agents either rely on explicit user instructions or engage in multi-turn clarification to elicit user p…

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Behavior2Trip：通过用户行为轨迹实现个性化旅行规划

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