Data Scaling Laws
Data Scaling Laws in Imitation Learning for Robotic Manipulation
- Scale
- 24098 trajectories Source-reported scale
- Formats
- Not declared
- License
- MIT
- Published
- 2025
Decision summary
Data Scaling Laws in Imitation Learning for Robotic Manipulation
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.
No source-backed day-level release date is published for this dataset. Its year is not being converted into an inferred event.
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
65/100
Provisional
1/6 dimensions scored · 24% 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
World-model observation, geometry, or temporal semantics are not verified.
Failure and recovery readiness
No verified failure/recovery annotation evidence is available yet.
Download and processing readiness
Scale is declared; transfer and processing estimates are not measured.
Review unresolved evidence and next checks
Signal gaps
- Observation / ego video. Not enough evidence is available to classify this signal.
- Gaze / attention. Not enough evidence is available to classify this signal.
- Language intent / task phase. 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.
Dataset facts
- Source
- Fanqi-Lin
- Evidence
- secondary claim
- Formats
- Not declared
- Source-reported scale
- 24098 trajectories
Loop signals
2/7 present or partial
No decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownView 5 more signal categories
Data Scaling Laws in Imitation Learning for Robotic Manipulation
partialNo decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownNo decision-grade evidence captured yet.
unknownUnknown · MIT
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.
curated official source
Integration notes
No integration notes are published.