LIBERO-RIG: A Hardware-Setup Robustness Benchmark for Vision-Language-Action Models

arXiv:2610.18843 · cs.RO, cs.AI · Submitted 2026-10-13 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-10-13

Updated: 2026-10-13

Comments: 30 pages (4 pages main text plus appendix), 15 figures, 18 tables

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes

Sources

• LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization
• robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
• $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
• X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model
• NORA: A Small Open-Sourced Generalist Vision Language Action Model for Embodied Tasks
• MolmoAct: Action Reasoning Models that can Reason in Space
• Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
• Causal World Modeling for Robot Control
• THE COLOSSEUM: A Benchmark for Evaluating Generalization for Robotic Manipulation
• Decomposing the Generalization Gap in Imitation Learning for Visual Robotic Manipulation
• VLABench: A Large-Scale Benchmark for Language-Conditioned Robotics Manipulation with Long-Horizon Reasoning Tasks

Related papers

• FMT x: An Efficient and Asymptotically Optimal Extension of the Fast Marching Tree for Dynamic Replanning
• MPCFormer: A physics-informed data-driven approach for explainable socially-aware autonomous driving
• RoboLab: A High-Fidelity Simulation Benchmark for Analysis of Task Generalist Policies
• ARC: A Reasoning Recipe for Robot Foundation Models
• HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
• APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies