Composition-RL: Compose Your Verifiable Prompts for Reinforcement Learning of Large Language Models
Composition-RL addresses limited verifiable prompts in Reinforcement Learning by automatically composing existing problems into new, more complex ones before training. This method, Composition-RL, mitigates the issue of easy prompts dominating training data by creating harder compositional prompts. Experiments show this approach consistently improves reasoning capability across various model sizes and benchmarks.