发表机构
Australian National University（澳大利亚国立大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出LLMs Unplugged，一套不插电活动，通过n-gram模型和加权采样教授LLM训练到生成循环，已惠及400多名参与者，资源免费开放。
AI 中文摘要
大型语言模型（LLMs）无处不在，然而许多学习者缺乏对其如何生成文本的具体心智模型。本文介绍了LLMs Unplugged，一套不插电活动，通过手工构建的n-gram模型和简单加权采样，教授从训练到生成的循环（及更深入的内容）。基于这些资源的工作坊已面向中学、高等教育及高管教育背景的400多名参与者开展，参与者反馈这些活动通过将LLMs重新定义为大规模概率性“下一个词生成”而使其不再神秘。所有资源均在知识共享许可下于该http URL免费提供，其模块化设计支持从一小时的速成课程到数天密集型工作坊的各种形式。
英文摘要
Large Language Models (LLMs) are everywhere, yet many learners lack a concrete mental model of how they generate text. This paper presents LLMs Unplugged, an unplugged set of activities that teaches the training-to-generation loop (and beyond) using hand-built n-gram models and simple weighted sampling. Workshops based on these resources have been delivered to over 400 participants across secondary, tertiary, and executive-education contexts, and participants report that the activities demystify LLMs by reframing them as probabilistic "next word generation" at scale. All resources are freely available under a Creative Commons license at www.llmsunplugged.org, with a modular design that supports anything from a one hour crash course to a several-day intensive workshop.
Comments8 pages. Published in Proceedings of the 28th Australasian Computing Education Conference (ACE 2026)
Journal refProceedings of the 28th Australasian Computing Education Conference (ACE 2026), Melbourne, VIC, Australia, February 9-13, 2026
