[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f7EXWFnnBOavdj5xi6mGmD1fpDT-uBptV_g2lVYgV9uo":3},{"answer":4,"createTime":5,"id":6,"options":7,"origin":12,"question":13,"related":14,"source":24,"type":35},[],"2026-01-12 22:14:15",1083011710,[8,9,10,11],"大型语言模型 (LLM)","记忆模块","工具模块","行动模块",{},"在AI大模型驱动的智能体中,提供核心认知与决策能力,被比作"大脑"的模块是?( )",[15,26,36,46,55,65,68,77,85,90],{"answer":16,"createTime":5,"id":17,"options":18,"question":23,"source":24,"type":25},[],1083011681,[19,20,21,22],"人类作者的主体责任","透明声明","保障原创性贡献","严格的内容核查与验证","在学术活动中使用AI辅助时,应遵循哪些基本原则以保障学术诚信?( )","v2",1,{"answer":27,"createTime":5,"id":28,"options":29,"question":34,"source":24,"type":35},[],1083011687,[30,31,32,33],"预训练 (Pre-training)","有监督微调 (SFT)","基于人类反馈的强化学习 (RLHF)","数据清洗","大语言模型训练流程中,主要目标是"对齐人类偏好与价值观"的阶段是?( )",0,{"answer":37,"createTime":5,"id":38,"options":39,"question":45,"source":24,"type":25},[],1083011689,[40,41,42,43,44],"信息处理的"加速器"与"组织者"","概念理解的"催化剂"与"多棱镜"","学习过程的"反馈器"与"陪练员"","创新思维的"点火器"与"发散器"","任务规划的"导航仪"与"分解器"","在认知策略层面,AI主要扮演的辅助角色有哪些?( )",{"answer":47,"createTime":5,"id":48,"options":49,"question":54,"source":24,"type":35},[],1083011698,[50,51,52,53],""流程赋能"",""完全替代"",""宏观启发"",""基础运算"","文本将AI在方法实践层的作用,从"点状辅助"向什么转变进行了描述?( )",{"answer":56,"createTime":57,"id":58,"options":59,"question":64,"source":24,"type":35},[],"2026-01-12 22:14:14",1083011706,[60,61,62,63],"图灵测试","中文房间","斯坦福小镇","薛定谔的猫","当一个AI系统在所有可观察的行为上都与拥有智能的系统无法区分时,是否就能认为它拥有智能?深刻挑战这一观点的思想实验是?( )",{"answer":66,"createTime":5,"id":6,"options":67,"question":13,"source":24,"type":35},[],[8,9,10,11],{"answer":69,"createTime":5,"id":70,"options":71,"question":76,"source":24,"type":35},[],1083011713,[72,73,74,75],"数据标注员","算法工程师","主导者与决策者","被动执行者","在方法实践层的人机协同中,哪一项被反复重申为人类的核心角色?( )",{"answer":78,"createTime":5,"id":79,"options":80,"question":83,"source":24,"type":84},[],1083011723,[81,82],"对","错","在利用AI进行内容梳理时,AI生成的结果是最终成品,可以完全替代学习者本人对原文的深入阅读和独立思考.( )",3,{"answer":86,"createTime":5,"id":87,"options":88,"question":89,"source":24,"type":84},[],1083011725,[81,82],"斯坦福小镇(Generative Agents)案例的核心贡献是展示了如何让智能体通过观察和模仿来学习操作智能手机上的各种应用程序.( )",{"answer":91,"createTime":5,"id":92,"options":93,"question":98,"source":24,"type":25},[],1083011742,[94,95,96,97],"清晰性","目标导向与迭代优化","任务分解","上下文提供","构建有效提示词的四大核心原则是什么?( )"]