arxiv
PublishedMay 14, 2026 at 4:00 AM
SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning
Publisher summary· verbatim
arXiv:2605.09423v2 Announce Type: replace Abstract: LLM/VLM-based digital agents have advanced rapidly thanks to scalable sandboxes for coding, web navigation, and computer use, which provide rich interactive training grounds. In contrast, embodied agents still lack abundant, diverse, and automatica
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 Learning8harxivSubagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks8harxivDistribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts8harxivIn RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning8hThe Bubble Brief
WEEKLYRead AI insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗