yuuu94
W2-VLA Offline CoT Labels
Frame-aligned offline chain-of-thought annotations for training vision-language-action policies on LIBERO, RoboTwin, and four real-world manipulation tasks. Contains annotations only; images, videos, and actions are not included.
Downloads0
Episodes4,573
Why This Matters for Physical AI
Provides structured chain-of-thought reasoning annotations to improve vision-language-action model interpretability and performance on robotic manipulation tasks across simulated and real-world environments.
Technical Profile
- Modalities
- language
- Environment
- simulationreal
- Task Types
- manipulationpick_and_place
- Episodes
- 4,573
- Data Format
- npz
- Annotation Types
- language_instructionschain_of_thought
Access
Need custom language data?
Claru builds purpose-built datasets for simulation applications with dense human annotations and quality assurance.
Request a Sample Pack