cs.LG（2024-11-30）

📊 共 11 篇论文 | 🔗 2 篇有代码

🎯 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) (4 🔗1) 支柱五：交互与反应 (Interaction & Reaction) (1) 支柱八：物理动画 (Physics-based Animation) (1 🔗1)

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

#	题目	一句话要点	标签	🔗	⭐
1	Approximate Fiber Product: A Preliminary Algebraic-Geometric Perspective on Multimodal Embedding Alignment	提出近似纤维积以解决多模态嵌入对齐问题	representation learning multimodal
2	Toward Fair Graph Neural Networks Via Dual-Teacher Knowledge Distillation	提出FairDTD，通过双教师知识蒸馏实现公平且高效的图神经网络。	representation learning distillation
3	A Unified Data Representation Learning for Non-parametric Two-sample Testing	提出RL-TST框架，用于非参数双样本检验中的统一数据表示学习	representation learning
4	Towards Fault Tolerance in Multi-Agent Reinforcement Learning	提出基于注意力机制和优先级采样的容错多智能体强化学习方法	reinforcement learning
5	Table Integration in Data Lakes Unleashed: Pairwise Integrability Judgment, Integrable Set Discovery, and Multi-Tuple Conflict Resolution	提出数据湖中表集成方法，解决可集成性判断、集合发现和冲突消解问题	contrastive learning large language model

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

#	题目	一句话要点	标签	🔗	⭐
6	On Foundation Models for Dynamical Systems from Purely Synthetic Data	提出基于纯合成数据的动态系统基础模型，提升泛化性和数据效率	foundation model
7	Rethinking Strategic Mechanism Design In The Age Of Large Language Models: New Directions For Communication Systems	利用大型语言模型革新通信系统中的策略机制设计	large language model
8	TAROT: Targeted Data Selection via Optimal Transport	提出TAROT，通过最优传输实现面向复杂目标域的数据选择。	multimodal	✅
9	Rank It, Then Ask It: Input Reranking for Maximizing the Performance of LLMs on Symmetric Tasks	提出基于输入重排序的方法，提升LLM在对称任务上的性能。	large language model

🔬 支柱五：交互与反应 (Interaction & Reaction) (1 篇)

#	题目	一句话要点	标签	🔗	⭐
10	MQFL-FHE: Multimodal Quantum Federated Learning Framework with Fully Homomorphic Encryption	提出MQFL-FHE框架，利用量子计算和多模态学习提升FHE联邦学习的性能。	OMOMO multimodal

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

#	题目	一句话要点	标签	🔗	⭐
11	The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning	构建大规模物理模拟数据集The Well，促进机器学习在物理系统建模中的应用。	spatiotemporal	✅

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