cs.AI(2024-07-06)

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支柱九:具身大模型 (Embodied Foundation Models) (8 🔗1) 支柱一:机器人控制 (Robot Control) (1)

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

#题目一句话要点标签🔗
1 LogicVista: Multimodal LLM Logical Reasoning Benchmark in Visual Contexts 提出LogicVista基准,评估多模态LLM在视觉环境下的逻辑推理能力 large language model multimodal
2 Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns? 提出BeyondX基准,揭示大语言模型在多未知数数学问题上的局限性,并提出Formulate-and-Solve策略。 large language model
3 MFE-ETP: A Comprehensive Evaluation Benchmark for Multi-modal Foundation Models on Embodied Task Planning MFE-ETP:用于具身任务规划的多模态基础模型综合评估基准 foundation model
4 Harnessing the Power of LLMs: Automating Unit Test Generation for High-Performance Computing 利用大语言模型,自动化生成高性能计算单元测试 large language model
5 Lucy: Think and Reason to Solve Text-to-SQL Lucy:结合LLM与自动推理,解决复杂数据库Text-to-SQL难题 large language model
6 Are LLMs Correctly Integrated into Software Systems? 研究揭示LLM与RAG集成软件系统中的缺陷模式并提出改进指南 large language model
7 Achieving Tool Calling Functionality in LLMs Using Only Prompt Engineering Without Fine-Tuning 仅用Prompt工程实现LLM的工具调用功能,无需微调 large language model
8 Algorithmic Language Models with Neurally Compiled Libraries 提出神经编译库增强算法语言模型,提升LLM的推理与规划能力 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 Form Forge: Latent Space Exploration of Architectural Forms via Explicit Latent Variable Manipulation Form Forge:通过显式潜在变量操纵探索建筑形式的潜在空间 manipulation

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