Entity dossier

Dataset dataset--syngrasp-1b

SynGrasp-1B

One billion synthetic VLA frames used to pretrain GraspVLA.

Reviewed relationships 1

  1. Verified

    GraspVLA Model trained on SynGrasp-1B

    Scope synthetic pretraining

    Boundary The source states one billion synthetic VLA frames; frames are not trajectories or hours.

    First observed · reviewed · [R17] · Show in graph

Canonical evidence claims 12

Claims are projected from authored tables. A dash remains an explicit missing value; it is never filled from a neighboring product or name match.

Robotics benchmarks — suite identity, not a ranking Robot Training Corpus 12 rows · 2 declared gaps

MetricValue and evidence
Claim boundaryframes are not hours or trajectories. Not DexGraspNet’s 1.32 million grasps [R17]
Embodiment in the sourcesynthetic grasping VLA frames; not a named robot SKU [R17]
Engine / renderer Declared gap
First public datearXiv 2025-05-06 [R17]
Kindsynthetic VLA pretraining frames used with GraspVLA [R17]
Language-conditionedsynthetic VLA frames with action data in the paper [R17]
Mediumsynthetic [R17]
PaperarXiv:2505.03233 [R17]
Primary metric familypretraining frames for GraspVLA [R17]
Public codepromised with GraspVLA; check the project page for release [R17]
Public leaderboard Declared gap
Published scale1 billion synthetic VLA frames [R17]

Source ledger 1

  1. [R17]ResearchGraspVLA — “a Grasping Foundation Model Pre-trained on Billion-scale Synthetic Action Data”. Type: research paper. ID: arXiv:2505.03233. Retrieved: 2026-08-26.Retrieved

What is not inferred

No fuzzy entity matching, adjacent-column borrowing, universal compatibility, commercial maturity, or checkpoint-to-product identity. Absence of a relation means unreviewed or unsupported here—not proven incompatibility.