World Action Agent: Harnessing VLMs for Robot Manipulation via World Action Rehearsal

arXiv:2609.29964 · cs.RO, cs.AI · Submitted 2026-09-24 · Read on arXiv

cs.RO, cs.AI

Submitted: 2026-09-24

Updated: 2026-09-24

Terminology

• World Action Agent — 39× in this paper
• Fine-Tuning — 12× in this paper · explained in 5 episodes
• Trace — 12× in this paper · explained in 2 episodes
• Grounding — 8× in this paper · explained in 3 episodes
• Verification — 8× in this paper · explained in 2 episodes
• Alignment — 7× in this paper · explained in 1 episode
• Calibration — 4× in this paper · explained in 7 episodes
• Agent Harness — 3× in this paper · explained in 1 episode
• Procedural Knowledge — 3× in this paper · explained in 2 episodes
• World Model — 3× in this paper · explained in 7 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Action Primitives — 2× in this paper · explained in 1 episode
• Adaptation — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Foundation Model — 2× in this paper · explained in 3 episodes
• Foundation Models — 2× in this paper · explained in 7 episodes
• Generalization — 2× in this paper · explained in 13 episodes
• IEEE International Conference on Robotics and Automation — 2× in this paper
• Point Clouds — 2× in this paper · explained in 2 episodes
• Vision-Language Models (VLMs) — 2× in this paper · explained in 6 episodes
• Vision-Language-Action (VLA) Models — 2× in this paper · explained in 2 episodes
• Adam — 1× in this paper · explained in 2 episodes
• Affordance — 1× in this paper · explained in 1 episode
• Agent Interactions — 1× in this paper · explained in 1 episode
• Agentic System — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Catastrophic Forgetting — 1× in this paper · explained in 5 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Core — 1× in this paper · explained in 2 episodes
• Cross-Embodiment Transfer — 1× in this paper · explained in 2 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Semantic Understanding — 1× in this paper · explained in 2 episodes
• Steering — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
• RoboScript: Code Generation for Free-Form Manipulation Tasks across Real and Simulation
• GaP: A Graph-as-Policy Multi-Agent Self-Learning Harness For Variational Automation Tasks
• Show-Harness: Just a VLM Agent Can Play Robots
• VIA: Visual Interface Agent for Robot Control
• $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
• Agent as Policy for Robotic Manipulation
• VISUALSKILL: Multimodal Skills for Computer-Use Agents
• OpenVLA: An Open-Source Vision-Language-Action Model
• Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
• Causal World Modeling for Robot Control
• Unified Video Action Model
• JEPA-WAM: Learning Vision-Language-Action Policies with Joint-Embedding World Modeling
• Sci-VLA: Agentic VLA Inference Plugin for Long-Horizon Tasks in Scientific Experiments
• World Action Models: A Survey
• Fast-WAM: Do World Action Models Need Test-time Future Imagination?
• Playful Agentic Robot Learning
• MMSkills: Towards Multimodal Skills for General Visual Agents
• Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents
• LIBERO-PRO: Towards Robust and Fair Evaluation of Vision-Language-Action Models Beyond Memorization

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