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News/MIPS: Mitigating Mode Collapse in Reinforcement Learning for Large Outcome Spaces
arxiv
PublishedOctober 15, 2026 at 4:00 AM

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

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arXiv:2610.19457v1 Announce Type: new 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. Inverse Probability Scaling (IPS) counters this

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