RealtimeWAM: One-Step Asynchronous World Action Models
cs.CV, cs.LG, cs.RO
Submitted: 2026-10-05
Updated: 2026-10-05
Code: https://github.com/ModelTC/lightx2v
Sources
- Flash-WAM: Modality-Aware Distillation for World Action Models
- Stochastic Interpolants: A Unifying Framework for Flows and Diffusions
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- Real-Time Execution of Action Chunking Flow Policies
- Training-Time Action Conditioning for Efficient Real-Time Chunking
- UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
- AHA-WAM:Asynchronous Horizon-Adaptive World-Action Modeling with Observation-Guided Context Routing
- WorldVLA: Towards Autoregressive Action World Model
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models
- Mean Flows for One-step Generative Modeling
- AsyncVLA: An Asynchronous VLA for Fast and Robust Navigation on the Edge
- LoRA: Low-Rank Adaptation of Large Language Models
- MeanFlowNFT: Bringing Forward-Process RL to Average-Velocity Generators
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- AsyncVLA: Asynchronous Flow Matching for Vision-Language-Action Models
- OpenVLA: An Open-Source Vision-Language-Action Model
- Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
- Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
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