Co-RL: Unsupervised Reasoning via Multi-Agent Reinforcement Learning

Co-RL enables unsupervised reasoning by using cooperative multi-agent training to derive reward signals from model completions. This approach mitigates the training collapse and bias common in single-model self-rewarding reinforcement learning.