arxiv
PublishedJuly 24, 2026 at 4:00 AM
—neutral
Offline RL with Hierarchical Action Chunking
Publisher summary· verbatim
arXiv:2607.20834v1 Announce Type: new Abstract: Offline goal-conditioned reinforcement learning (RL) holds the promise of learning general-purpose policies from static datasets. However, scaling these methods to long-horizon tasks remains a challenge due to the curse of horizon, where value estimati
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
arxivOPTScientist: Multi-Agent Discovery of Typed Optimizer Programs for Transformer Pretraining5harxivMore Is Not More: What Matters for Diversity in LLM Opinions?5harxivEvaluation and Prognostic Validation of Deep Regression Models for WSI-Based Gene-Expression Prediction5harxivSESaMo: Symmetry-Enforcing Stochastic Modulation for Normalizing Flows5hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗