cs.AI（2024-08-14）

📊 共 11 篇论文

🎯 兴趣领域导航

支柱九：具身大模型 (Embodied Foundation Models) (8) 支柱一：机器人控制 (Robot Control) (1) 支柱八：物理动画 (Physics-based Animation) (1) 支柱二：RL算法与架构 (RL & Architecture) (1)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (8 篇)

#题目一句话要点标签🔗⭐
1 An Efficient and Explanatory Image and Text Clustering System with Multimodal Autoencoder Architecture 提出基于多模态自编码器的图像文本聚类系统，用于分析不同文化对国际新闻事件的解读。 multimodal
2 Transformers and Large Language Models for Efficient Intrusion Detection Systems: A Comprehensive Survey 综述Transformer与LLM在入侵检测系统中的应用，提升网络安全效率。 large language model
3 Development of a Large Language Model-based Multi-Agent Clinical Decision Support System for Korean Triage and Acuity Scale (KTAS)-Based Triage and Treatment Planning in Emergency Departments 构建基于LLM的多智能体临床决策支持系统，提升急诊科KTAS分诊和治疗规划。 large language model
4 A System for Automated Unit Test Generation Using Large Language Models and Assessment of Generated Test Suites AgoneTest：一个基于大语言模型的自动化单元测试生成与评估系统 large language model
5 CodeMirage: Hallucinations in Code Generated by Large Language Models CodeMirage：研究大型语言模型在代码生成中的幻觉现象，并提出基准数据集。 large language model
6 Training Overhead Ratio: A Practical Reliability Metric for Large Language Model Training Systems 提出训练开销比率(TOR)，用于评估大规模语言模型训练系统的可靠性 large language model
7 Re-Thinking Process Mining in the AI-Based Agents Era 提出基于AI Agent工作流的流程挖掘方法，提升LLM在复杂场景下的推理能力。 large language model
8 SAGE-RT: Synthetic Alignment data Generation for Safety Evaluation and Red Teaming SAGE-RT：用于安全评估和红队测试的合成对齐数据生成 large language model

🔬 支柱一：机器人控制 (Robot Control) (1 篇)

#题目一句话要点标签🔗⭐
9 The Complexity of Manipulation of k-Coalitional Games on Graphs 研究k-联盟图博弈中操纵行为的复杂性，并提出社会感知操纵方法 manipulation

🔬 支柱八：物理动画 (Physics-based Animation) (1 篇)

#题目一句话要点标签🔗⭐
10 Abstract Operations Research Modeling Using Natural Language Inputs 提出NL2OR，利用大语言模型从自然语言输入自动生成运筹学模型 AMP large language model

🔬 支柱二：RL算法与架构 (RL & Architecture) (1 篇)

#题目一句话要点标签🔗⭐
11 Improving Global Parameter-sharing in Physically Heterogeneous Multi-agent Reinforcement Learning with Unified Action Space 针对物理异构多智能体强化学习，提出统一动作空间以提升全局参数共享效率。 reinforcement learning

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