World-Calibrated Proposal-to-Action Flow for Vision-Language-Action Models
cs.RO, cs.CV
Submitted: 2026-10-01
Updated: 2026-10-01
Code: https://github.com/JiuTian-VL/ProAct
Project page: https://jiutian-vl.github.io/ProAct-page
Terminology
Sources
- V-JEPA 2: Self-Supervised Video Models Enable Understanding, Prediction and Planning
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- UniVLA: Learning to Act Anywhere with Task-centric Latent Actions
- AHA-WAM:Asynchronous Horizon-Adaptive World-Action Modeling with Observation-Guided Context Routing
- Xiaomi-Robotics-0: An Open-Sourced Vision-Language-Action Model with Real-Time Execution
- WorldVLA: Towards Autoregressive Action World Model
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing
- LIBERO-Plus: In-depth Robustness Analysis of Vision-Language-Action Models
- Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising
- From Abstraction to Instantiation: Learning Behavioral Representation for Vision-Language-Action Model
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- Action-to-Action Flow Matching
- Streaming Flow Policy: Simplifying diffusion/flow-matching policies by treating action trajectories as flow trajectories
- Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
- Causal World Modeling for Robot Control
- Global Prior Meets Local Consistency: Dual-Memory Augmented Vision-Language-Action Model for Efficient Robotic Manipulation
- HoloBrain-0 Technical Report
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