arXiv cs.CL· Andres Karjus·· 7 天前AI 评分20
大语言模型、机器辅助文化分析与智能体转向
Large Language Models, Machine-Assisted Cultural Analytics, and the Agentic Turn
AI 导读
大语言模型让文化材料更易转化为可分析变量，LLM 驱动的智能体系统则将机器辅助延伸至研究流程的其他环节。作者认为，这些技术扩大了研究规模、方法范围与可委托范围，但测量支撑文化论断的基本逻辑大体未变。该章节并非操作指南或近期 LLM 用例综述，而是审视这一新范式的关键面向与整体图景。
正文 · 原文
Abstract:Technologies like large language models make it easier to convert cultural material into analyzable variables, while LLM-driven agentic systems extend machine assistance to other parts of the research workflow. Rather than a full how-to guide or an exhaustive review of recent LLM use cases, this chapter looks at some crucial aspects of this new paradigm as well as the bigger picture. I argue that these technologies expand the scale, methodological range, and scope for delegation, while the basic logic by which those measurements support cultural claims remains mostly unchanged.
| Subjects: | Computers and Society (cs.CY); Computation and Language (cs.CL) |
| Cite as: | arXiv:2610.12792 [cs.CY] |
| (or arXiv:2610.12792v1 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2610.12792 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Andres Karjus [view email]
[v1]
Thu, 8 Oct 2026 22:54:57 UTC (186 KB)
来源：arXiv cs.CL · arxiv.org