EO-1
IPEC / EO-Robotics
A unified embodied model using interleaved vision-text-action pretraining for perception, reasoning, planning, and continuous robot control.
Unified reasoning and action
Paired with EO-Data1.5M and EO-Bench; keep training and benchmark relations explicit.
A model hub link is a declaration. Files, loadability, evaluation, and deployment are scored separately.
Model decision scorecard
Use-case scores and evidence confidence are separate; Unknown is not treated as failure.
Code, weights, and checkpoints
UsefulAn official model hub is linked; weight files and loadability are not verified.
Loading and training reproducibility
UnknownNo verified loading configuration is available.
Training data requirements
UsefulRequired signal categories are declared; exact tensor and action interfaces still need verification.
Evaluation evidence
UsefulEvaluation focus is declared, but metrics are not independently verified.
Deployment readiness
UnknownHardware, latency, dependencies, and runtime loading are not yet verified.
Artifact facts and provenance
No metadata-verified artifact facts yet. Source links remain declarations only.
Loop signal demand
Signals this model family needs for training, evaluation, or failure mining.
Observation / ego video
observation
Language intent / task phase
language intent · task phase
Action / robot state
actions · Interleaved vision-text-action samples · Continuous robot actions · Unified reasoning and action
Future state / dynamics
future state
Feedback / correction / failure
Evaluation prompts
Sim-real / embodiment metadata
Continuous robot actions · Robot-control transfer
Evaluation focus
- Unified reasoning and action
- Embodied multimodal understanding
- Robot-control transfer
Missing critical loop signals
Core signal demands are represented. Check quality, alignment, and access constraints.
Related catalog datasets
EO-Data1.5M
Interleaved embodied reasoning and robot-control pretraining
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
Open X-Embodiment
Cross-embodiment robot learning in a unified format
Exact action dimensions, control frequency, normalization, and camera mapping require interface verification.
AgiBot World 2026
Large-scale real-world humanoid interaction data
Dataset license restricts commercial use.
OpenBot notes
- Paired with EO-Data1.5M and EO-Bench; keep training and benchmark relations explicit.