14K-Example Data Recipe Boosts Long-Context RL Without Reward Engineering

A data-centric approach using ~14K examples across three task families — retrieval, multi-evidence synthesis, and reasoning — paired with a minimal GRPO setup substantially improves long-context reasoning in LLMs. The work challenges the assumption that reward engineering is the primary lever for RL-based long-context improvement.