cs.LG(2024-09-16)

📊 共 5 篇论文 | 🔗 3 篇有代码

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支柱九:具身大模型 (Embodied Foundation Models) (3 🔗2) 支柱二:RL算法与架构 (RL & Architecture) (2 🔗1)

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

#题目一句话要点标签🔗
1 Benchmarking Large Language Model Uncertainty for Prompt Optimization 提出LLM提示优化不确定性基准,评估并改进不确定性度量以提升优化效果 large language model
2 RetrievalAttention: Accelerating Long-Context LLM Inference via Vector Retrieval RetrievalAttention:通过向量检索加速长文本LLM推理,降低显存占用。 large language model
3 CSKV: Training-Efficient Channel Shrinking for KV Cache in Long-Context Scenarios CSKV:面向长文本场景,通过高效通道缩减压缩KV缓存,降低训练成本。 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🔗
4 Quantile Regression for Distributional Reward Models in RLHF 提出分位数奖励模型(QRM),通过学习奖励分布提升RLHF中奖励模型的表达能力。 reinforcement learning RLHF large language model
5 SHIRE: Enhancing Sample Efficiency using Human Intuition in REinforcement Learning SHIRE:利用人类直觉增强强化学习的样本效率,应用于机器人控制。 reinforcement learning deep reinforcement learning optical flow

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