OS-Genesis
Interaction-driven pipeline that synthesizes mobile and web GUI agent trajectories without human supervision or predefined tasks, via reverse task synthesis and a trajectory reward model.
AI-assisted editorial review against a primary source. This is a catalog annotation, not an independent reproduction or endorsement.
What is this resource?
- Resource type
- Datasets
- Environment
- cross-platform
- Topics
- data-generation
- Record publication date
- Not recorded
- Evidence retrieved
- 2026-10-16T06:36:01Z
- Resource ID
- github:os-copilot/os-genesis
What licenses are recorded?
Code, training data, weights, and documents can have different terms. A blank declaration means unknown, not unrestricted use.
- Code
- Not recorded
- Data
- Not recorded
- Document
- Not recorded
- Weights
- Not recorded
Dataset profile
- Supervision
- reverse task synthesis, GUI action trajectories
- Modalities
- screenshots, text, actions
- Formats
- JSONL trajectories, JSON transition triples
- Splits
- Not recorded
Scale and counting units
Not recordedThe repository links distinct AndroidControl-oriented, AndroidWorld-oriented, and web training files plus raw pre-state/action/post-state triples. These are training artifacts, not a documented train/test split, and related representations are not disjoint corpus totals. No numerical inventory is asserted from release names or linked archives.
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Primary evidence and verification
Source retrieval is separate from experiment reproduction. Use the original publication or publisher page when citing claims about the resource.
- editorial primary review
Retrieved 2026-10-16T06:36:01Z. Supports: name, kind, summary, environments, topics, scope, relations, details.
Content fingerprint
430e495ab250395d666854bd18b0fc29b819cd784cd7730215ef65e461834d0d - editorial primary review
Retrieved 2026-10-16T06:36:01Z. Supports: details.dataset_profile.
Content fingerprint
430e495ab250395d666854bd18b0fc29b819cd784cd7730215ef65e461834d0d - editorial primary review
Retrieved 2026-10-16T06:36:58Z. Supports: details.dataset_profile.
Content fingerprint
c87e97eb397da04806d53145cf9c13be739fc657bb54dca9318c8c4ed2a36249
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