RLSVR Extends Verifiable Rewards to Open-Ended Tasks

RLSVR introduces a task-transformation-based training paradigm that enables Reinforcement Learning with Verifiable Rewards to move beyond mathematics and coding. This method allows for self-improvement in open-ended tasks by constructing pretext tasks that derive supervision from the data itself, bypassing the need for human preference models.