Accelerate RL rollouts by up to 50% with distribution-aware speculative decoding

Distribution-aware speculative decoding (DAS) is a framework that reduces rollout time in RL post-training by up to 50% without altering model outputs.

It uses a training-free adaptive suffix tree drafter and a length-aware scheduling strategy to handle stragglers and exploit historical trajectory data.