DataFlex-RL: An Evaluation Platform for RLVR Data Policies
The paper introduces DataFlex‑RL, a platform to benchmark how different data‑selection policies affect reinforcement‑learning‑with‑verifiable‑rewards training. Across extensive experiments on Qwen2.5‑7B and Llama‑3.1‑8B, uniform sampling is the only method that consistently improves performance, and no alternative policy yields a statistically significant gain.











