cs.AI(2023-12-15)
📊 共 11 篇论文
🎯 兴趣领域导航
支柱九:具身大模型 (Embodied Foundation Models) (6)
支柱二:RL算法与架构 (RL & Architecture) (4)
支柱一:机器人控制 (Robot Control) (1)
🔬 支柱九:具身大模型 (Embodied Foundation Models) (6 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | KGLens: Towards Efficient and Effective Knowledge Probing of Large Language Models with Knowledge Graphs | 提出KGLens以高效有效地探测大型语言模型的知识盲点 | large language model | ||
| 2 | Distilling Large Language Models for Matching Patients to Clinical Trials | 利用大语言模型蒸馏,实现患者与临床试验的高效匹配 | large language model | ||
| 3 | Prompting Large Language Models for Topic Modeling | 提出PromptTopic,利用大语言模型进行主题建模,解决短文本和语义忽略问题。 | large language model | ||
| 4 | VoCopilot: Voice-Activated Tracking of Everyday Interactions | VoCopilot:语音激活的日常交互追踪系统,实现端到端对话洞察。 | large language model | ||
| 5 | InstructPipe: Generating Visual Blocks Pipelines with Human Instructions and LLMs | InstructPipe:利用人类指令和LLM生成可视化块流水线 | large language model | ||
| 6 | Grounding for Artificial Intelligence | 研究AI的“具身性”,为通用人工智能奠定基础 | large language model |
🔬 支柱二:RL算法与架构 (RL & Architecture) (4 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 7 | Robustness Verification of Deep Reinforcement Learning Based Control Systems using Reward Martingales | 提出基于奖励鞅的深度强化学习控制系统鲁棒性验证方法 | reinforcement learning deep reinforcement learning DRL | ||
| 8 | Deep Reinforcement Learning for Joint Cruise Control and Intelligent Data Acquisition in UAVs-Assisted Sensor Networks | 提出基于深度强化学习的联合巡航控制与智能数据采集方法,用于无人机辅助传感器网络。 | reinforcement learning deep reinforcement learning | ||
| 9 | Multi-agent Reinforcement Learning: A Comprehensive Survey | 综述多智能体强化学习,应对共享环境中智能决策的挑战。 | reinforcement learning | ||
| 10 | Situation-Dependent Causal Influence-Based Cooperative Multi-agent Reinforcement Learning | 提出基于情境依赖因果影响的合作多智能体强化学习算法 | reinforcement learning |
🔬 支柱一:机器人控制 (Robot Control) (1 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 11 | Constrained Meta-Reinforcement Learning for Adaptable Safety Guarantee with Differentiable Convex Programming | 提出基于可微凸规划的约束元强化学习,实现非平稳环境下安全适应性 | manipulation reinforcement learning |