Decision summary
Unified reasoning and action
Hardware, latency, dependencies, and checkpoint loading are not pipeline-tested.
Run a checkpoint loading smoke test before marking the model pipeline-tested.
Evidence profile
A visual read of adoption evidence. Scores describe catalog evidence readiness, not task performance.
Published evaluation
5/6
dimensions scored
Unknown evidence remains visible and is never treated as a zero.
Why these scores
The strongest decision reasons behind the evidence profile.
Artifact availability
UsefulCheckpoint files were verified in the official repository metadata.
Training and loading reproducibility
UsefulConfiguration files are present; runtime loading is not tested.
Evaluation evidence
UnknownNo structured evaluation evidence has been verified.
Data requirements
Declared loop-data needs, missing evidence, and the next checks that matter.
Observation / ego video
observation
Language intent / task phase
language intent · task phase
Action / robot state
actions
Future state / dynamics
future state
Critical gaps
Core categories are represented. Interface alignment and data quality still require verification.
Linked datasets
Signal-level links only. Verify runtime interfaces before use.
More evidenceShowHide
Additional data signals
Sim-real / embodiment metadata
Descriptive model record
Additional decision dimensions
Access and license are declared by the source.
75 · c85Required signal categories are structured; exact tensor and action interfaces still need verification.
76 · c70Hardware, latency, dependencies, and checkpoint loading are not pipeline-tested.
70 · c55Artifact facts
- release_year
- official_claim
- 2025
- curated official source year
- model.required_signals
- official_claim
- observation · language intent · task phase · actions · future state
- Official model documentation and curated signal mapping
- model.hub
- official_claim
- declared
- curated model hub link
- model.weight_files
- metadata_verified
- repository: IPEC-COMMUNITY/EO-1-3B · count: 2 · sample files: model-00001-of-00002.safetensors · model-00002-of-00002.safetensors
- Hugging Face model metadata siblings
- model.checkpoint_files
- metadata_verified
- repository: IPEC-COMMUNITY/EO-1-3B · count: 2 · sample files: model-00001-of-00002.safetensors · model-00002-of-00002.safetensors
- Hugging Face model metadata checkpoint files
- model.config_files
- metadata_verified
- repository: IPEC-COMMUNITY/EO-1-3B · count: 5 · sample files: config.json · generation_config.json · preprocessor_config.json · processor_config.json · tokenizer_config.json
- Hugging Face model metadata siblings
- license.weights
- metadata_verified
- mit
- Hugging Face model card license metadata
- license
- metadata_verified
- mit
- Hugging Face model card license metadata
- release_timing
- metadata_verified
- 2025-08-28T17:26:15.000Z
- arXiv 2508.21112 published
- discovery.source
- secondary_claim
- name: worldbench/awesome-embodied-data-pyramid · trust: discovery_only · revision: 0568599d0619f20946e8089f6a941d0d9e30b690
- #table-embodied-foundation-models-vla-wam, table 17, row 28
- discovery.raw_fields
- secondary_claim
- Time: 2025.8 · Method: EO-1 · Institution: Shanghai AI Lab · Project: [](https://eo-robotics.ai/eo-1) · Model: VLA · Data: ![Real][data-real] ![General][data-general]
- #table-embodied-foundation-models-vla-wam, table 17, row 28
- model.reported_release_time
- secondary_claim
- 2025.8
- #table-embodied-foundation-models-vla-wam, table 17, row 28
- model.type
- secondary_claim
- VLA
- #table-embodied-foundation-models-vla-wam, table 17, row 28
- model.training_data_layers
- secondary_claim
- real_robot · general
- #table-embodied-foundation-models-vla-wam, table 17, row 28
- model.institution
- secondary_claim
- Shanghai AI Lab
- #table-embodied-foundation-models-vla-wam, table 17, row 28
- catalog.curation
- secondary_claim
- tier: editorial_focus · collection: WorldBench Awesome Embodied Data Pyramid · policy: human_curated_priority
- #table-embodied-foundation-models-vla-wam, table 17, row 28
Additional references
OpenBot notes
- Paired with EO-Data1.5M and EO-Bench; keep training and benchmark relations explicit.
