1Step-WAM: Your World Action Model but Faster using 1-Step Action Generation
cs.CV
Submitted: 2026-10-11
Updated: 2026-10-11
Code: https://github.com/changdong1687/1Step-WAM
Sources
- Flash-WAM: Modality-Aware Distillation for World Action Models
- World Simulation with Video Foundation Models for Physical AI
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- One Step Diffusion via Shortcut Models
- CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers
- OpenVLA: An Open-Source Vision-Language-Action Model
- Causal World Modeling for Robot Control
- One-Step Flow Policy: Self-Distillation for Fast Visuomotor Policies
- Flow Matching for Generative Modeling
- LIBERO: Benchmarking Knowledge Transfer for Lifelong Robot Learning
- SnapFlow: One-Step Action Generation for Flow-Matching VLAs via Progressive Self-Distillation
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- Consistency Policy: Accelerated Visuomotor Policies via Consistency Distillation
- Progressive Distillation for Fast Sampling of Diffusion Models
- SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
- Consistency Models
- Galaxea Open-World Dataset and G0 Dual-System VLA Model
- Gemini Robotics: Bringing AI into the Physical World
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