RecastVLA: From Past Interaction to Future Control with Adaptive Policy States
cs.RO
Submitted: 2026-09-26
Updated: 2026-09-26
Terminology
Sources
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- Zeva: In-Context Causal Learning for Generalizable Embodied Manipulation
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- RoboDojo: A Unified Sim-and-Real Benchmark for Comprehensive Evaluation of Generalist Robot Manipulation Policies
- Addressing Some Limitations of Transformers with Feedback Memory
- WAM-TTT: Steering World-Action Models by Watching Human Play at Test Time
- Coordination Among Neural Modules Through a Shared Global Workspace
- RoboTTT: Context Scaling for Robot Policies
- OpenVLA: An Open-Source Vision-Language-Action Model
- GR00T N1: An Open Foundation Model for Generalist Humanoid Robots
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- StarVLA: A Lego-like Codebase for Vision-Language-Action Model Developing
- MEM: Multi-Scale Embodied Memory for Vision Language Action Models
- Beyond Data Scaling: Representation-Centric Continued Pre-training for Vision-Language-Action Models
- ABot-M0: VLA Foundation Model for Robotic Manipulation with Action Manifold Learning
- Fast-WAM: Do World Action Models Need Test-time Future Imagination?
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