arxiv
PublishedJune 17, 2026 at 4:00 AM
—neutral
Learning Upper Lower Value Envelopes to Shape Online RL: A Principled Approach
Publisher summary· verbatim
arXiv:2510.19528v2 Announce Type: replace-cross Abstract: We investigate the fundamental problem of leveraging offline data to accelerate online reinforcement learning - a direction with strong potential but limited theoretical grounding. Our study centers on how to \emph{learn} and \emph{apply} val
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivBringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning9harxivSubagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks9harxivDistribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts9harxivIn RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning9hThe Bubble Brief
WEEKLYRead reinforcement-learning insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗