{ "schema_version": 1, "annotation_revision": 2, "annotation_status": "user_confirmed_release", "source_dataset": { "repo_id": "wzlllong/value-model-benchmark-training-data", "subtree": "data/simulation/one-shot", "data_revision": "43ae4845fe0461c66aa59a0ee441185d99fb05f8", "source_subtree_tree_id": "837e271aac36ea3eea72599ab5bca86db64bb025" }, "dataset": { "codebase_version": "v3.0", "fps": 25, "total_episodes": 15, "total_frames": 8080, "total_videos": 45 }, "paper": { "url": "https://arxiv.org/abs/2610.26663", "revision": "2610.26663v1", "section": "C.2 Task Descriptions and Subtask Decomposition" }, "segment_count": 58, "paper_subtask_count": 58, "annotation_target": "Active semantic subtask for each training-demonstration frame; not success, reward, or task-completion probability.", "release_scope": "Supplemental annotations for simulation One-Shot training demonstrations, separate from benchmark test-set labels described in paper Section 3.4.", "coverage_policy": "Every frame receives one printed paper subtask. Initial waiting belongs to the first subtask; terminal tail and retraction belong to the final subtask through episode end.", "interval_convention": "[start_frame, end_frame); inclusive_end_frame = end_frame - 1", "join_keys": [ "episode_index", "frame_index" ], "global_index_check": "global_index equals the LeRobot data index column", "timestamp_convention": "Nominal timestamp_seconds = frame_index / 25; associate frames by integer keys, not exact float timestamp equality.", "boundary_band": "Typically 13 frames (0.52 seconds); retained segment-specific widths are suggested adjustment bands, not measured confidence bounds or guarantees of frame-perfect precision.", "boundary_uncertain_policy": "For each segment, mark its first t frames after an internal start and last t frames before an internal end; episode outer boundaries excluded. Keep all frame labels regardless of mask.", "video_loading": { "recommended_lerobot": "0.4.2", "recommended_pyav": "15.1.0", "default_tolerance_seconds": 0.0001, "semantic_band_changes_loader_tolerance": false }, "source_training_payload_modified": false, "printed_label_policy": "Use the paper's printed S definitions, including Press By Number's S1 first button, S2 blue, S3 second button, S4 blue again; preserve the accepted order without rewriting the paper instruction.", "task_aliases": { "sweep_objects": "sweep_blocks" }, "episodes": [ { "episode_index": 0, "task_index": 0, "task_key": "arrange_largest_number", "source_task_key": "arrange_largest_number", "length": 579, "dataset_from_index": 0, "dataset_to_index": 579 }, { "episode_index": 1, "task_index": 1, "task_key": "fill_pen_holder", "source_task_key": "fill_pen_holder", "length": 934, "dataset_from_index": 579, "dataset_to_index": 1513 }, { "episode_index": 2, "task_index": 2, "task_key": "fold_clothes", "source_task_key": "fold_clothes", "length": 301, "dataset_from_index": 1513, "dataset_to_index": 1814 }, { "episode_index": 3, "task_index": 3, "task_key": "hang_mugs", "source_task_key": "hang_mugs", "length": 513, "dataset_from_index": 1814, "dataset_to_index": 2327 }, { "episode_index": 4, "task_index": 4, "task_key": "insert_tubes", "source_task_key": "insert_tubes", "length": 320, "dataset_from_index": 2327, "dataset_to_index": 2647 }, { "episode_index": 5, "task_index": 5, "task_key": "make_toast", "source_task_key": "make_toast", "length": 584, "dataset_from_index": 2647, "dataset_to_index": 3231 }, { "episode_index": 6, "task_index": 6, "task_key": "organize_table", "source_task_key": "organize_table", "length": 839, "dataset_from_index": 3231, "dataset_to_index": 4070 }, { "episode_index": 7, "task_index": 7, "task_key": "pack_objects_into_box", "source_task_key": "pack_objects_into_box", "length": 414, "dataset_from_index": 4070, "dataset_to_index": 4484 }, { "episode_index": 8, "task_index": 8, "task_key": "play_stacking_toy", "source_task_key": "play_stacking_toy", "length": 888, "dataset_from_index": 4484, "dataset_to_index": 5372 }, { "episode_index": 9, "task_index": 9, "task_key": "press_by_number", "source_task_key": "press_by_number", "length": 378, "dataset_from_index": 5372, "dataset_to_index": 5750 }, { "episode_index": 10, "task_index": 10, "task_key": "put_bottles_into_dustbin", "source_task_key": "put_bottles_into_dustbin", "length": 363, "dataset_from_index": 5750, "dataset_to_index": 6113 }, { "episode_index": 11, "task_index": 11, "task_key": "stack_blocks", "source_task_key": "stack_blocks", "length": 268, "dataset_from_index": 6113, "dataset_to_index": 6381 }, { "episode_index": 12, "task_index": 12, "task_key": "store_laptop_and_headphones", "source_task_key": "store_laptop_and_headphones", "length": 551, "dataset_from_index": 6381, "dataset_to_index": 6932 }, { "episode_index": 13, "task_index": 13, "task_key": "swap_blocks", "source_task_key": "swap_blocks", "length": 445, "dataset_from_index": 6932, "dataset_to_index": 7377 }, { "episode_index": 14, "task_index": 14, "task_key": "sweep_blocks", "source_task_key": "sweep_objects", "length": 703, "dataset_from_index": 7377, "dataset_to_index": 8080 } ] }