Causal-History Test-Time Scaling for Failure Recovery in Autoregressive World-Action Models
cs.RO
Submitted: 2026-09-16
Updated: 2026-09-16
Terminology
Sources
- RT-1: Robotics Transformer for Real-World Control at Scale
- World Action Models are Zero-shot Policies
- RedFlow: Redirect Failure into Action-level Corrections for Flow-matching VLA Policy
- SAIL: Test-Time Scaling for In-Context Imitation Learning with VLM
- Video Prediction Policy: A Generalist Robot Policy with Predictive Visual Representations
- Fast-WAM: Do World Action Models Need Test-time Future Imagination?
- AHA-WAM:Asynchronous Horizon-Adaptive World-Action Modeling with Observation-Guided Context Routing
- Steering Vision-Language-Action Models as Anti-Exploration: A Test-Time Scaling Approach
- Is the Future Compatible? Diagnosing Dynamic Consistency in World Action Models
- ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning
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
- HRDexDB: A 4D Dexterous Grasping Dataset Across Human and Multiple Robot Embodiments
- APT: Action Expert Pretraining Improves Instruction Generalization of Vision-Language-Action Policies
- Fine-tuning is Not Enough: A Parallel Framework for Collaborative Imitation and Reinforcement Learning in End-to-end Autonomous Driving