Generalists Act, Specialists Intervene: Modular Stage-Selective Reinforcement Learning for Vision-Language-Action Manipulation

arXiv:2609.26467 · cs.RO · Submitted 2026-09-22 · Read on arXiv

cs.RO

Submitted: 2026-09-22

Updated: 2026-10-08

Comments: 8 pages, 5 figures, 4 tables. Extended version of the paper accepted at the IROS 2026 International Workshop on Industrial Applications of Robot Learning (IARL), with expanded multi-backbone evaluation, robustness analysis, and autonomous real-robot experiments

Code: https://github.com/RLinf/RLinf

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

Terminology

• Actor — 8× in this paper · explained in 3 episodes
• Reinforcement Learning — 8× in this paper · explained in 4 episodes
• Ablation — 6× in this paper · explained in 1 episode
• Adaptation — 4× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Affordance — 2× in this paper · explained in 1 episode
• Distribution Shift — 2× in this paper · explained in 5 episodes
• Human-in-the-Loop — 2× in this paper · explained in 3 episodes
• Latent Space — 2× in this paper · explained in 7 episodes
• Reinforcement Learning (RL) — 2× in this paper · explained in 25 episodes
• Representation Learning — 2× in this paper · explained in 2 episodes
• Steering — 2× in this paper · explained in 2 episodes
• Transformer — 2× in this paper · explained in 2 episodes
• VLA Models — 2× in this paper · explained in 3 episodes
• Action Space — 1× in this paper · explained in 1 episode
• Agentic AI — 1× in this paper · explained in 1 episode
• Benchmark — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Conference on Automation Science and Engineering — 1× in this paper
• Decode — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Failure Modes — 1× in this paper · explained in 3 episodes
• Flow Matching — 1× in this paper · explained in 8 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Grounding — 1× in this paper · explained in 3 episodes
• Hysteresis — 1× in this paper · explained in 3 episodes
• Online Adaptation — 1× in this paper · explained in 3 episodes
• Phase Transitions — 1× in this paper · explained in 2 episodes
• World Model — 1× in this paper · explained in 7 episodes

Sources

• WireCraft: A Simulation Benchmark for Industrial DLO Manipulation
• RL Token: Bootstrapping Online RL with Vision-Language-Action Models
• Foresight Residual RL for Long-Horizon Robot Manipulation with Vision-Language-Action Models
• SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics

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• 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