Efficient Federated RLHF via Zeroth-Order Policy Optimization
arXiv:2604.17747v1 Announce Type: new
Abstract: This paper considers reinforcement learning from human feedback in a federated learning setting with resource-constrained agents, such as edge devices. We propose an efficient federated RLHF algorithm, n…