cs.AI(2024-03-12)
📊 共 7 篇论文 | 🔗 2 篇有代码
🎯 兴趣领域导航
支柱九:具身大模型 (Embodied Foundation Models) (4 🔗1)
支柱二:RL算法与架构 (RL & Architecture) (2 🔗1)
支柱四:生成式动作 (Generative Motion) (1)
🔬 支柱九:具身大模型 (Embodied Foundation Models) (4 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 1 | Online Continual Learning For Interactive Instruction Following Agents | 提出在线持续学习方法以提升交互指令跟随智能体的能力 | instruction following | ✅ | |
| 2 | The future of document indexing: GPT and Donut revolutionize table of content processing | 提出基于GPT和Donut的自动化文档索引方法以解决信息提取瓶颈 | large language model | ||
| 3 | Couler: Unified Machine Learning Workflow Optimization in Cloud | 提出Couler以解决云端机器学习工作流优化问题 | large language model | ||
| 4 | Transforming Competition into Collaboration: The Revolutionary Role of Multi-Agent Systems and Language Models in Modern Organizations | 提出多智能体系统与语言模型结合以提升组织决策能力 | large language model |
🔬 支柱二:RL算法与架构 (RL & Architecture) (2 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 5 | An Improved Strategy for Blood Glucose Control Using Multi-Step Deep Reinforcement Learning | 提出多步深度强化学习策略以改善血糖控制 | reinforcement learning deep reinforcement learning DRL | ||
| 6 | A Question-centric Multi-experts Contrastive Learning Framework for Improving the Accuracy and Interpretability of Deep Sequential Knowledge Tracing Models | 提出问题中心的多专家对比学习框架以提升知识追踪模型的准确性与可解释性 | contrastive learning | ✅ |
🔬 支柱四:生成式动作 (Generative Motion) (1 篇)
| # | 题目 | 一句话要点 | 标签 | 🔗 | ⭐ |
|---|---|---|---|---|---|
| 7 | Vector Quantization for Deep-Learning-Based CSI Feedback in Massive MIMO Systems | 提出基于深度学习的CSI反馈方法以优化大规模MIMO系统 | VQ-VAE |