Use supported HTML alignment wrappers for the overview numeric headers and values. Preserve neutral text, domain markers and all content outside this table in both languages.
Replace colored episode-count image badges with aligned bold numbers and place episode units in the headers. Keep blue/orange domain markers and preserve all content outside the first overview table in both languages.
3 days ago
Polish bilingual dataset overview and training guidance
Add aggregate episode, synchronized-time-step and camera-video totals; clarify the automatic HF video preview; refine source and training wording while preserving tables, task definitions, visual assets and tested code.
Clarify simulation source wording in subset documentation
Use recorded again to describe demonstrations collected again. Update only the corresponding README checksum entries; all training payload and provenance are preserved.
Document verified per-task counts and PyTorch training batches
Confirm exactly 100 train episodes per Full-Shot task and one per One-Shot task, add the locally executed DataLoader example and domain-specific model dimensions, and pin downloads to the release with synchronized subset documentation.
Align all four subset READMEs with the RoboValue dataset card
Use inline symbols for chapter and metric labels, and combine counts with their units in blue-purple and warm-orange badges. Preserve bilingual text, task names, numeric values, code examples, catalog, and all data subsets.
Keep dataset visual markers inline with headings and table labels
Use blue-purple simulation and warm real-world markers, emphasize episode counts, and add compact semantic icons to section headings and primary statistics tables. Preserve all card text, numerical values, reading examples, catalog, and data subsets.
Fix inline emphasis in bilingual dataset root description
Document ARX and AgiBot Genie02, reviewed and recollected simulation sources, common trajectory contents, and unified displayed simulation task names. Align bilingual card layout with the RoboValue project README and provide a locally executed LeRobot 0.4.2 example. Training data and provenance remain unchanged.
Clean dataset card into definitive dataset descriptions
Remove release-process narration, minor alignment-row history and provisional wording; retain dataset scope, schemas, task mappings, source attribution and reading instructions. State authorized public release and verified RoboDojo-source licensing. No training data changed.
Present simulation before real-world and complete dataset card guidance
Preserve the overview, domain, layout and download structure; reorder both languages and catalog; document all four released subsets, pinned loading, statistics and One-Shot task correspondence. Training data subtrees remain unchanged.
Document verified Real-World One-Shot training release
