cs.LG(2024-07-02)

📊 共 4 篇论文

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支柱二:RL算法与架构 (RL & Architecture) (3) 支柱九:具身大模型 (Embodied Foundation Models) (1)

🔬 支柱二:RL算法与架构 (RL & Architecture) (3 篇)

#题目一句话要点标签🔗
1 PWM: Policy Learning with Multi-Task World Models PWM:基于多任务世界模型的策略学习,提升多embodiment强化学习效率 reinforcement learning policy learning world model
2 Cost-Effective Proxy Reward Model Construction with On-Policy and Active Learning 提出基于在线策略和主动学习的低成本代理奖励模型构建方法,降低人机反馈强化学习的标注成本。 reinforcement learning RLHF DPO
3 A Contrastive Learning Based Convolutional Neural Network for ERP Brain-Computer Interfaces 提出基于对比学习的卷积神经网络,用于提升脑机接口中ERP信号的跨个体泛化能力。 contrastive learning spatiotemporal

🔬 支柱九:具身大模型 (Embodied Foundation Models) (1 篇)

#题目一句话要点标签🔗
4 LLM-Select: Feature Selection with Large Language Models LLM-Select:利用大型语言模型进行特征选择,性能媲美传统数据科学方法 large language model

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