APRIL (Active Partial Rollouts In reinforcement Learning) addresses the long-tail generation problem in RL-based LLM training.
When training LLMs with RL, some rollouts generate extremely long sequences that become stragglers — holding up the entire batch. APRIL solves this with system-level optimizations for scalable LLM post-training.