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float32
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116
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int64
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79
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2
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2.866667
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2.9
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2.966667
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3
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3.033333
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3.066667
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3.1
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3.133333
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3.166667
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3.2
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3.233333
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3.266667
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3.3
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End of preview. Expand in Data Studio

This dataset was created using LeRobot.

MolmoAct2-BimanualYAM Dataset

This repository is one subset of the MolmoAct2-BimanualYAM Dataset, a large-scale collection of bimanual robot manipulation demonstrations collected for MolmoAct2. Across the full collection, MolmoAct2-BimanualYAM contains more than 720 hours of training demonstrations spanning diverse tabletop manipulation tasks.

Language Annotations

This dataset includes annotated language instructions in meta/tasks_annotated.parquet. The file is indexed by episode_index and has a task column containing our per-episode annotated instruction.

The standard LeRobot loader resolves a frame's language instruction through task_index: each data row stores a task_index, which is looked up in meta/tasks.parquet. When you use these annotations, load meta/tasks_annotated.parquet and look up the current episode_index instead. If no valid annotated row is available, fall back to the standard LeRobot task.

Visualization

Use the MolmoAct2 LeRobot Visualizer to inspect episodes from this dataset, including camera streams, robot state, actions, and language annotations.

Citation

@misc{fang2026molmoact2actionreasoningmodels,
      title={MolmoAct2: Action Reasoning Models for Real-world Deployment},
      author={Haoquan Fang and Jiafei Duan and Donovan Clay and Sam Wang and Shuo Liu and Weikai Huang and Xiang Fan and Wei-Chuan Tsai and Shirui Chen and Yi Ru Wang and Shanli Xing and Jaemin Cho and Jae Sung Park and Ainaz Eftekhar and Peter Sushko and Karen Farley and Angad Wadhwa and Cole Harrison and Winson Han and Ying-Chun Lee and Eli VanderBilt and Rose Hendrix and Suveen Ellawela and Lucas Ngoo and Joyce Chai and Zhongzheng Ren and Ali Farhadi and Dieter Fox and Ranjay Krishna},
      year={2026},
      eprint={2605.02881},
      archivePrefix={arXiv},
      primaryClass={cs.RO},
      url={https://arxiv.org/abs/2605.02881},
}

Dataset Structure

meta/info.json:

{
    "codebase_version": "v3.0",
    "robot_type": "bi_yam_follower",
    "total_episodes": 80,
    "total_frames": 148255,
    "total_tasks": 1,
    "chunks_size": 1000,
    "data_files_size_in_mb": 100,
    "video_files_size_in_mb": 500,
    "fps": 30,
    "splits": {
        "train": "0:80"
    },
    "data_path": "data/chunk-{chunk_index:03d}/file-{file_index:03d}.parquet",
    "video_path": "videos/{video_key}/chunk-{chunk_index:03d}/file-{file_index:03d}.mp4",
    "features": {
        "action": {
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            "names": [
                "left_joint_0.pos",
                "left_joint_1.pos",
                "left_joint_2.pos",
                "left_joint_3.pos",
                "left_joint_4.pos",
                "left_joint_5.pos",
                "left_gripper.pos",
                "right_joint_0.pos",
                "right_joint_1.pos",
                "right_joint_2.pos",
                "right_joint_3.pos",
                "right_joint_4.pos",
                "right_joint_5.pos",
                "right_gripper.pos"
            ],
            "shape": [
                14
            ]
        },
        "observation.state": {
            "dtype": "float32",
            "names": [
                "left_joint_0.pos",
                "left_joint_1.pos",
                "left_joint_2.pos",
                "left_joint_3.pos",
                "left_joint_4.pos",
                "left_joint_5.pos",
                "left_gripper.pos",
                "right_joint_0.pos",
                "right_joint_1.pos",
                "right_joint_2.pos",
                "right_joint_3.pos",
                "right_joint_4.pos",
                "right_joint_5.pos",
                "right_gripper.pos"
            ],
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        },
        "observation.images.right": {
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            ],
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            ],
            "info": {
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                "video.width": 640,
                "video.codec": "av1",
                "video.pix_fmt": "yuv420p",
                "video.is_depth_map": false,
                "video.fps": 30,
                "video.channels": 3,
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        "observation.images.left": {
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        "observation.images.top": {
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                "video.channels": 3,
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            }
        },
        "timestamp": {
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            "shape": [
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            "names": null
        },
        "frame_index": {
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        },
        "episode_index": {
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        },
        "index": {
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        },
        "task_index": {
            "dtype": "int64",
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            "names": null
        }
    }
}
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