HarnessRL: Co-Evolving Policies with a Just-in-Time Training Harness for Open-Ended RL

What this work does

HarnessRL jointly adapts task sampling, privileged rollout guidance, and reward rubrics during policy training. A memory-backed proposer and critic seek to maintain useful learning signals as policy capabilities change.