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Manipulation datasetOpenReadiness 73/100Provisional

MolmoAct2 Bimanual YAM Dataset

A large-scale bimanual manipulation dataset collected by Ai2 for MolmoAct2 using paired YAM follower arms. It contains 32,246 episodes (76M frames) spanning 34 tabletop tasks with 720+ hours of teleoperated…

Source notes

A large-scale bimanual manipulation dataset collected by Ai2 for MolmoAct2 using paired YAM follower arms. It contains 32,246 episodes (76M frames) spanning 34 tabletop tasks with 720+ hours of teleoperated demonstrations. Each episode provides three RGB camera views (left, right, top) plus 14-dim joint/gripper states, in LeRobot format with per-episode annotated language instructions.

Scale
720 hours
Formats
lerobot
License
Apache-2.0
Published
2026-05-04
Embodiments
yam
Modalities
language, proprioception, rgb
Official sourceAudit a local copy

Decision summary

Best for

teleoperation

Main blocker

Metadata requires review against the official source before publication.

Next check

Read the dataset manifest and feature schema.

Release history

Source-backed release timing for this canonical dataset record.

Important releases

  1. Dataset series published

    Release timing is recorded from official dataset metadata.

    Release evidence

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 work

73/100

Provisional

4/6 dimensions scored · 48% confidence

Access and governance75conf. 85
Schema and signal coverageNot scoredconf. 15
Policy training readiness85conf. 55
World-model readiness68conf. 50
Failure and recovery readinessNot scoredconf. 15
Download and processing readiness65conf. 65
Read the evidence behind all 6 dimensions

Access and governance

Access and license are declared by the source.

usefulfit 75 · confidence 85

Schema and signal coverage

No machine-readable schema has been verified yet.

unknownnot scored · confidence 15

Policy training readiness

Observation and action/state signals are declared; alignment quality still depends on sample verification.

usefulfit 85 · confidence 55

World-model readiness

Temporal observations plus geometry or semantic context are declared; sample alignment remains to be audited.

usefulfit 68 · confidence 50

Failure and recovery readiness

No verified failure/recovery annotation evidence is available yet.

unknownnot scored · confidence 15

Download and processing readiness

Scale is declared; transfer and processing estimates are not measured.

usefulfit 65 · confidence 65
Review unresolved evidence and next checks

Signal gaps

  • 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
Engineering checksBronze

Needs Audit

6/12checks passed

OBRS metadata and reported test evidence. A breakdown behind Selection readiness, not a separate score or an independent OpenBot certification.

Standardization & Loaders15 / 25 pt
Physical & Action Quality8 / 25 pt
Semantic & Annotation20 / 20 pt
Real-World Validation0 / 15 pt
License & Compliance10 / 15 pt
Missing evidence and readiness gaps
  • A passing real-hardware test report is required.
  • A passing ingestion/pipeline test report is required.
  • A passing privacy and provenance review is required.

Dataset facts

Source
Allen Institute for AI (Ai2)
Evidence
secondary claim
Formats
lerobot
episodes
32.2K
hours
720
tasks
34
Read paper

Loop signals

4/7 present or partial

Gaze / attention

No decision-grade evidence captured yet.

unknown
Feedback / correction / failure

No decision-grade evidence captured yet.

unknown
View 5 more signal categories
Observation / ego video

video · A large-scale bimanual manipulation dataset collected by Ai2 for MolmoAct2 using paired YAM follower arms. It contains 32,246 episodes (76M frames) spanning 34 tabletop tasks with 720+ hours of teleoperated demonstrations. Each episode provides three RGB camera views (left, right, top) plus 14-dim joint/gripper states, in LeRobot format with per-episode annotated language instructions.

present
Action / hand pose / robot state

A large-scale bimanual manipulation dataset collected by Ai2 for MolmoAct2 using paired YAM follower arms. It contains 32,246 episodes (76M frames) spanning 34 tabletop tasks with 720+ hours of teleoperated demonstrations. Each episode provides three RGB camera views (left, right, top) plus 14-dim joint/gripper states, in LeRobot format with per-episode annotated language instructions.

partial
Language intent / task phase

language · A large-scale bimanual manipulation dataset collected by Ai2 for MolmoAct2 using paired YAM follower arms. It contains 32,246 episodes (76M frames) spanning 34 tabletop tasks with 720+ hours of teleoperated demonstrations. Each episode provides three RGB camera views (left, right, top) plus 14-dim joint/gripper states, in LeRobot format with per-episode annotated language instructions.

present
Sim-real pairing

No decision-grade evidence captured yet.

unknown
License / format / access

Open · Apache-2.0 · lerobot

present
Evidence details and provenance

Official signal claims

LanguageProprioceptionVideo

Schema and annotations

No machine-readable schema facts are captured.

Sample verification

Pending. Metadata does not prove sample coverage, alignment, or file integrity.

curated official source

Integration notes

  • Metadata requires review against the official source before publication.