Author

Georgia Chalvatzaki

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Preprint Sep 2026

Find Something You Can't Do: Agentic Real-World Reinforcement Learning for Self-Improving VLA Models

Vision--language--action (VLA) models provide strong priors for robotic manipulation but are typically deployed as frozen policies, unable to improve from their own failures. Real-world reinforcement learning (RL) offers a path to continued improvement, yet manual environment resets and task-success supervision hinder...

Yuan Fang, Ze-Chu Li, Hao-Lei Tong et al. · 0 citations

Jul 2026

Globalized Constrained Stein Variational Inference for Diverse Feasible Robot Motion Planning

SteinSQP (Stein Variational Sequential Quadratic Programming), a constrained Stein variational inference method for diverse feasible robot motion sampling, shows faster and more robust ensemble convergence in terms of iterations, improves particle-wise feasibility, and achieves faster batched time-to-solution on challe...

Jiayun Li, Georgia Chalvatzaki · arXiv.org · 1 citation