Rho: A Foundation for Efficiently Adaptable VLA Models
cs.RO
Submitted: 2026-09-29
Updated: 2026-09-29
Code: https://github.com/microsoft/rhobotics
Project page: https://microsoft.github.io/rhobotics
Terminology
Sources
- $\pi^{*}_{0.6}$: a VLA That Learns From Experience
- Phi-4-reasoning-vision-15B Technical Report
- $\pi_0$: A Vision-Language-Action Flow Model for General Robot Control
- Real-Time Execution of Action Chunking Flow Policies
- GR-2: A Generative Video-Language-Action Model with Web-Scale Knowledge for Robot Manipulation
- PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis
- RoboTwin 2.0: A Scalable Data Generator and Benchmark with Strong Domain Randomization for Robust Bimanual Robotic Manipulation
- InternVLA-M1: A Spatially Guided Vision-Language-Action Framework for Generalist Robot Policy
- Universal Manipulation Interface: In-The-Wild Robot Teaching Without In-The-Wild Robots
- Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better
- Learning Universal Policies via Text-Guided Video Generation
- MolmoAct2: Action Reasoning Models for Real-world Deployment
- Benchmarking Affordance Generalization with BusyBox
- VLA-0: Building State-of-the-Art VLAs with Zero Modification
- TwinVLA: Data-Efficient Bimanual Manipulation with Twin Single-Arm Vision-Language-Action Models
- $\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization
- ${\pi}_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities
- Fine-Tuning Vision-Language-Action Models: Optimizing Speed and Success
- Cosmos Policy: Fine-Tuning Video Models for Visuomotor Control and Planning
- Robot Learning as an Empirical Science: Best Practices for Policy Evaluation
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