QF3 introduces an off-policy update for flow-policy reinforcement learning

QF3’s announcement describes a single off-policy update for training humanoids from scratch and fine-tuning VLAs and image models. Another researcher describes the approach as climbing Q-gradients, filtering for stability and flow-matching a replay buffer, and says it is sample-efficient.