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English(EN) PsyMemBehav: Psychology-Informed and Memory-Grounded Two-Level Identity-to-Action Reasoning for Social-Media Behavior Simulation

新AI模型利用心理学和记忆模拟社交媒体行为

研究人员开发了PsyMemBehav,一个旨在通过整合心理学特征和记忆检索来模拟社交媒体行为的新系统。该系统将用户描述符和记忆映射到在Reddit、Bluesky和X等平台上进行评论、点赞或转发等行为。为了训练和评估PsyMemBehav,创建了一个名为PsyMemBehav-bench的数据集,该数据集包含来自5800多名真实用户的557万条行为数据。实验表明,与GPT-5.4相比,PsyMemBehav显著提高了响应质量,并在群体行为模拟方面取得了优越的性能。 AI

影响 这项研究可能催生出更复杂的AI代理,能够理解和预测人类在社交平台上的行为。

排序理由 该集群描述了一篇关于用于社交媒体行为模拟的新型AI模型和数据集的详细研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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新AI模型利用心理学和记忆模拟社交媒体行为

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该集群描述了一篇关于用于社交媒体行为模拟的新型AI模型和数据集的详细研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Wenji Zhang, Xilong Cheng, Yunxiao Qin, Mai Tu, Tongye Zhu, Yuhao Zhou, JingBo Ji, Yuting Tan, Duoyin Li, Hongjiang Xiao, Yuan Zhang ·

    PsyMemBehav:心理学启发的、记忆驱动的、双层身份到行为的推理,用于社交媒体行为模拟

    arXiv:2610.14570v1 Announce Type: new Abstract: Large language models (LLMs) support social simulation, but faithfully reproducing real users requires grounding both structured platform decisions and language in sparse, noisy behavioral evidence. We introduce PsyMemBehav, which m…