cs.LG（2024-10-23）

📊 共 8 篇论文 | 🔗 1 篇有代码

🎯 兴趣领域导航

支柱二：RL算法与架构 (RL & Architecture) (4) 支柱九：具身大模型 (Embodied Foundation Models) (2 🔗1) 支柱一：机器人控制 (Robot Control) (1) 支柱三：空间感知与语义 (Perception & Semantics) (1)

🔬 支柱二：RL算法与架构 (RL & Architecture) (4 篇)

#	题目	一句话要点	标签	🔗	⭐
1	Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models	提出异步RLHF，加速并优化语言模型离线强化学习训练。	RLHF DPO large language model
2	Adaptive Segment-level Reward: Bridging the Gap Between Action and Reward Space in Alignment	提出自适应段落级别奖励，弥合对齐中动作与奖励空间差距	reinforcement learning large language model
3	Differentially Private Learning Needs Better Model Initialization and Self-Distillation	DPRefine通过改进初始化和自蒸馏提升差分隐私语言模型的效用性	distillation
4	Identifiable Representation and Model Learning for Latent Dynamic Systems	针对智能航天器，提出基于可控规范型的可辨识隐变量动态系统学习方法	latent dynamics

🔬 支柱九：具身大模型 (Embodied Foundation Models) (2 篇)

#	题目	一句话要点	标签	🔗	⭐
5	CoreInfer: Accelerating Large Language Model Inference with Semantics-Inspired Adaptive Sparse Activation	CoreInfer：基于语义的自适应稀疏激活加速大语言模型推理	large language model
6	MobileSafetyBench: Evaluating Safety of Autonomous Agents in Mobile Device Control	MobileSafetyBench：评估移动设备控制中自主Agent的安全性	large language model	✅

🔬 支柱一：机器人控制 (Robot Control) (1 篇)

#	题目	一句话要点	标签	🔗	⭐
7	Multimodal Information Bottleneck for Deep Reinforcement Learning with Multiple Sensors	提出多模态信息瓶颈模型以提升强化学习样本效率	locomotion reinforcement learning deep reinforcement learning

🔬 支柱三：空间感知与语义 (Perception & Semantics) (1 篇)

#	题目	一句话要点	标签	🔗	⭐
8	Incremental Learning of Affordances using Markov Logic Networks	提出MLN-CLA算法，用于机器人环境中物体可供性的增量学习与零样本推理。	affordance

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