cs.AI（2023-11-22）

📊 共 13 篇论文 | 🔗 3 篇有代码

🎯 兴趣领域导航

支柱九：具身大模型 (Embodied Foundation Models) (7 🔗1) 支柱二：RL算法与架构 (RL & Architecture) (3 🔗1) 支柱一：机器人控制 (Robot Control) (1) 支柱三：空间感知与语义 (Perception & Semantics) (1 🔗1) 支柱五：交互与反应 (Interaction & Reaction) (1)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (7 篇)

#题目一句话要点标签🔗⭐
1 Multimodal Large Language Models: A Survey 综述多模态大语言模型以解决数据理解不足问题 large language model multimodal
2 AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations 提出AlignedCoT以解决大语言模型提示效果不佳的问题 large language model chain-of-thought ✅
3 Towards Responsible Generative AI: A Reference Architecture for Designing Foundation Model based Agents 提出参考架构以设计基础模型驱动的智能体 large language model foundation model
4 Applying Large Language Models to Power Systems: Potential Security Threats 分析大型语言模型在电力系统中的潜在安全威胁 large language model
5 Large Language Models in Education: Vision and Opportunities 探讨大语言模型在教育中的应用以解决个性化学习问题 large language model
6 Conditions for Length Generalization in Learning Reasoning Skills 提出长度泛化条件以解决推理技能学习问题 large language model
7 Can LLMs Fix Issues with Reasoning Models? Towards More Likely Models for AI Planning 利用大型语言模型改进自动规划中的模型空间问题 large language model

🔬 支柱二：RL算法与架构 (RL & Architecture) (3 篇)

#题目一句话要点标签🔗⭐
8 Large Language Model as a Policy Teacher for Training Reinforcement Learning Agents 提出基于大语言模型的策略教师以提升强化学习代理的训练效率 reinforcement learning embodied AI large language model ✅
9 Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning 提出Nova以解决汇编代码分析中的信息稀疏问题 contrastive learning large language model
10 Quantum learning and essential cognition under the traction of meta-characteristics in an open world 提出开放世界模型以解决人工智能探索未知知识的问题 world model world models

🔬 支柱一：机器人控制 (Robot Control) (1 篇)

#题目一句话要点标签🔗⭐
11 Algorithmic Transparency and Manipulation 提出无视观点以解析算法透明度的操控潜力 manipulation

🔬 支柱三：空间感知与语义 (Perception & Semantics) (1 篇)

#题目一句话要点标签🔗⭐
12 Physical Reasoning and Object Planning for Household Embodied Agents 提出COAT框架以解决家庭智能体的物体替代选择问题 affordance large language model ✅

🔬 支柱五：交互与反应 (Interaction & Reaction) (1 篇)

#题目一句话要点标签🔗⭐
13 Enigma: Application-Layer Privacy for Quantum Optimization on Untrusted Computers 提出Enigma以解决量子优化中的隐私保护问题 OMOMO

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