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English(EN) LLMs for Social Network Modeling: From Network Generation to Dynamic Processes

调查梳理了大语言模型在社交网络建模中的应用,并强调了其偏见

一篇新发表在arXiv上的调查论文详细介绍了大语言模型(LLMs)在社交网络建模中的应用。该论文将现有研究分为网络生成和动态过程模型两类,强调了大语言模型模拟上下文感知社交行为和语言驱动交互的能力。虽然大语言模型比传统方法提供了更现实的途径,但该调查也指出了固有的社会偏见和提示敏感性等局限性,并概述了未来的研究方向。 AI

影响 提供了大语言模型在社交网络分析中应用的结构化概述,明确了关键挑战和未来研究途径。

排序理由 该集群包含一篇关于大语言模型在特定研究领域应用的调查论文。 [lever_c_demoted from research: ic=1 ai=1.0]

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调查梳理了大语言模型在社交网络建模中的应用,并强调了其偏见

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该集群包含一篇关于大语言模型在特定研究领域应用的调查论文。 [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) · Shikha Mallick, Alex Thomo, Akrati Saxena ·

    用于社交网络建模的大语言模型:从网络生成到动态过程

    arXiv:2609.08049v1 Announce Type: cross Abstract: Large language models (LLMs) are rapidly emerging as a new paradigm for modeling social networks by representing users and their relationships and interactions through natural language. Unlike classical network models or deep lear…