2 papers
cs.LG2026
Efficient Federated RLHF via Zeroth-Order Policy Optimization
Deyi Wang, Qining Zhang, Lei Ying
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 fede…
cs.LG2024
Zeroth-Order Policy Gradient for Reinforcement Learning from Human Feedback without Reward Inference
Qining Zhang, Lei Ying
Reward inference (learning a reward model from human preferences) is a critical intermediate step in the Reinforcement Learning from Human Feedback (RLHF) pipeline for fine-tuning…