EO-Bench
EO-Bench: Embodied Reasoning Benchmark for Vision-Language Models
Source notes
EO-Bench: Embodied Reasoning Benchmark for Vision-Language Models
Overview
EO-Bench is a comprehensive benchmark designed to evaluate the embodied reasoning capabilities of vision-language models (VLMs) in robotics scenarios. This benchmark is part of the EO-1 project, which develops unified embodied foundation models for general robot control. The benchmark assesses model performance across 12 distinct embodied reasoning categories, covering… See the full description on the dataset page: https://huggingface.co/datasets/IPEC-COMMUNITY/EO-Bench.
- Scale
- Not declared
- Formats
- Not declared
- License
- apache-2.0
- Published
- 2025-12-07
- Embodiments
- Not declared
- Modalities
- Not declared
Decision summary
library:datasets
No verified blocker is published; unresolved facts remain unknown.
Read the dataset manifest and feature schema.
Release history
Source-backed release timing for this canonical dataset record.
- Release evidence
Dataset published
Release timing is recorded from the official source creation date.
Selection readiness
6 evidence dimensions for deciding whether this dataset is ready to inspect, compare, or adopt. This is not a model benchmark.
Catalog evidence · not task performance
How scores work68/100
Provisional
1/6 dimensions scored · 21% confidence
Read the evidence behind all 6 dimensions
Access and governance
Access and license are declared by the source.
Schema and signal coverage
No machine-readable schema has been verified yet.
Policy training readiness
Observation/action alignment has not been established.
World-model readiness
Temporal observations plus geometry or semantic context are declared; sample alignment remains to be audited.
Failure and recovery readiness
No verified failure/recovery annotation evidence is available yet.
Download and processing readiness
Dataset scale and sampling path are unknown.
Review unresolved evidence and next checks
Signal gaps
- Action / hand pose / robot state. Not enough evidence is available to classify this signal.
- Gaze / attention. Not enough evidence is available to classify this signal.
- Feedback / correction / failure. Not enough evidence is available to classify this signal.
- Sim-real pairing. Not enough evidence is available to classify this signal.
Next checks
- Read the dataset manifest and feature schema.
- Run a bounded sample audit before assigning Strong readiness.
Engineering checks (OBRS) behind this record
Needs Audit
OBRS metadata and reported test evidence. A breakdown behind Selection readiness, not a separate score or an independent OpenBot certification.
- A passing real-hardware test report is required.
- A passing ingestion/pipeline test report is required.
- A passing privacy and provenance review is required.
Loop signals
3/7 present or partial
No decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownView 5 more signal categories
video · task_categories:image-to-text · modality:image
presentlanguage · task_categories:image-to-text · language:en · vision-language
presentNo decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownUnknown · apache-2.0
partialEvidence details and provenance
Official signal claims
Schema and annotations
No machine-readable schema facts are captured.
Sample verification
Pending. Metadata does not prove sample coverage, alignment, or file integrity.
README/card declaration
Integration notes
No integration notes are published.