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English(EN) LiveSim: Simulating Environment-Shaped Users in Multi-Agent Live-Stream Ecosystems

LiveSim框架使用LLM模拟直播生态系统中不断演变的用户行为

作者 PulseAugur 编辑部 · [4 个来源] ·

研究人员开发了LiveSim，一个利用大型语言模型（LLM）模拟多智能体直播生态系统中用户行为的新框架。与依赖静态用户画像的先前模拟器不同，LiveSim将用户表示为通过交互进行精炼的动态行为假设。这种方法捕捉了用户行为如何在社会环境中演变，从而能够更准确地模拟生态系统动态和平台干预的效果。在真实世界数据上进行的实验证明了LiveSim在提高用户行为保真度和实现生态系统层面分析方面的有效性。 AI

影响 能够更准确地模拟直播环境中复杂的社会动态和平台干预。

排序理由 该集群描述了一篇详细介绍新模拟框架的研究论文。

在 Hugging Face Daily Papers 阅读 →

AI 生成摘要 · Google Gemini · 来自 4 个来源。 我们如何撰写摘要 →

LiveSim框架使用LLM模拟直播生态系统中不断演变的用户行为

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该集群描述了一篇详细介绍新模拟框架的研究论文。
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报道来源 [4]

  1. arXiv cs.AI TIER_1 English(EN) · Jiaqi Xu, Yiran Qiao, Jing Chen, Qiwei Zhong, Xiang Ao, Xueqi Cheng ·

    LiveSim：模拟多智能体直播生态系统中受环境塑造的用户

    arXiv:2608.26849v1 Announce Type: new Abstract: User behavior simulation with large language models~(LLMs) is increasingly used to support multi-agent ecosystem simulation. Existing simulators typically rely on static user profiles inferred from historical observations, which bec…

  2. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Xueqi Cheng ·

    LiveSim：在多智能体直播生态系统中模拟受环境塑造的用户

    User behavior simulation with large language models~(LLMs) is increasingly used to support multi-agent ecosystem simulation. Existing simulators typically rely on static user profiles inferred from historical observations, which become inadequate in socially intensive environment…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    LiveSim：在多智能体直播生态系统中模拟受环境塑造的用户

    User behavior simulation with large language models~(LLMs) is increasingly used to support multi-agent ecosystem simulation. Existing simulators typically rely on static user profiles inferred from historical observations, which become inadequate in socially intensive environment…

  4. arXiv cs.MA (Multiagent) TIER_1 English(EN) · Xueqi Cheng ·

    LiveSim：模拟多智能体直播生态系统中受环境塑造的用户

    User behavior simulation with large language models~(LLMs) is increasingly used to support multi-agent ecosystem simulation. Existing simulators typically rely on static user profiles inferred from historical observations, which become inadequate in socially intensive environment…

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