cs.LG（2024-07-20）

📊 共 9 篇论文

🎯 兴趣领域导航

支柱二：RL算法与架构 (RL & Architecture) (5) 支柱九：具身大模型 (Embodied Foundation Models) (3) 支柱八：物理动画 (Physics-based Animation) (1)

🔬 支柱二：RL算法与架构 (RL & Architecture) (5 篇)

#	题目	一句话要点	标签	🔗	⭐
1	Is Behavior Cloning All You Need? Understanding Horizon in Imitation Learning	证明行为克隆在特定条件下可实现与在线模仿学习相当的性能	imitation learning behavior cloning
2	EEGMamba: Bidirectional State Space Model with Mixture of Experts for EEG Multi-task Classification	提出EEGMamba，首个基于双向状态空间模型和混合专家模型的通用脑电多任务分类网络。	Mamba state space model
3	FMamba: Mamba based on Fast-attention for Multivariate Time-series Forecasting	FMamba：结合快速注意力机制的Mamba模型用于多元时间序列预测	predictive model Mamba state space model
4	Teach Harder, Learn Poorer: Rethinking Hard Sample Distillation for GNN-to-MLP Knowledge Distillation	提出硬度感知蒸馏框架HGMD，解决GNN到MLP知识蒸馏中的硬样本瓶颈问题	distillation
5	Meta-GPS++: Enhancing Graph Meta-Learning with Contrastive Learning and Self-Training	Meta-GPS++：结合对比学习和自训练增强图元学习，解决少样本节点分类问题。	contrastive learning

🔬 支柱九：具身大模型 (Embodied Foundation Models) (3 篇)

#	题目	一句话要点	标签	🔗	⭐
6	All Against Some: Efficient Integration of Large Language Models for Message Passing in Graph Neural Networks	E-LLaGNN：高效整合大语言模型增强图神经网络消息传递	large language model
7	Understanding the Relationship between Prompts and Response Uncertainty in Large Language Models	提出提示-响应概念模型，理解大语言模型中提示信息与响应不确定性之间的关系	large language model
8	Designing Algorithms Empowered by Language Models: An Analytical Framework, Case Studies, and Insights	提出LLM算法分析框架，优化LLM驱动的复杂AI系统设计	large language model

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

#	题目	一句话要点	标签	🔗	⭐
9	Enhancing Wildfire Forecasting Through Multisource Spatio-Temporal Data, Deep Learning, Ensemble Models and Transfer Learning	提出基于多源时空数据、深度学习和集成迁移学习的野火预测方法	spatiotemporal

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