Showing 2025Show all
2 papers · 1 filter
cs.LG2025
Diffusion Models for Reinforcement Learning: Foundations, Taxonomy, and Development
Changfu Xu, Jianxiong Guo, Yuzhu Liang +7
Diffusion Models (DMs), as a leading class of generative models, offer key advantages for reinforcement learning (RL), including multi-modal expressiveness, stable training, and tr…
cs.LG2025
FedHL: Federated Learning for Heterogeneous Low-Rank Adaptation via Unbiased Aggregation
Zihao Peng, Jiandian Zeng, Boyuan Li +3
Federated Learning (FL) facilitates the fine-tuning of Foundation Models (FMs) using distributed data sources, with Low-Rank Adaptation (LoRA) gaining popularity due to its low com…