MIPS: Mitigating Mode Collapse in Reinforcement Learning for Large Outcome Spaces.

arXiv:2610.19457v1 Announce Type: cross Abstract: Expected-reward maximization in reinforcement learning concentrates probability mass on a few outcomes, even in tasks that require many distinct, high-quality solutions, a failure known as mode collapse. Invers