cs.LG（2024-05-24）

📊 共 6 篇论文 | 🔗 1 篇有代码

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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)

🔬 支柱九：具身大模型 (Embodied Foundation Models) (4 篇)

#题目一句话要点标签🔗⭐
1 Basis Selection: Low-Rank Decomposition of Pretrained Large Language Models for Target Applications 提出基于基选择的低秩分解方法，用于压缩LLM以适应特定应用。 large language model
2 Athena: Efficient Block-Wise Post-Training Quantization for Large Language Models Using Second-Order Matrix Derivative Information Athena：利用二阶矩阵导数信息高效量化大型语言模型 large language model
3 Transformers represent belief state geometry in their residual stream Transformer在残差流中以线性方式表征信念状态几何结构，蕴含未来信息。 large language model
4 Pipeline Parallelism with Controllable Memory 提出可控内存的流水线并行框架，显著提升大模型训练吞吐量。 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 Understanding the differences in Foundation Models: Attention, State Space Models, and Recurrent Neural Networks 提出动态系统框架DSF，统一分析Attention、SSM和RNN，揭示高效Foundation Model设计原则。 SSM state space model linear attention
6 Intelligent Go-Explore: Standing on the Shoulders of Giant Foundation Models Intelligent Go-Explore：利用大型预训练模型解决复杂探索问题 reinforcement learning foundation model

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