X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model
Paper
• 2510.10274 • Published
• 16
Search is not available for this dataset
observation.state listlengths 96 96 | action listlengths 14 14 | time_stamp float32 0 414 | timestamp float32 0 508 | frame_index int64 0 10.2k | episode_index int64 0 1.54k | index int64 0 2.85M | task_index int64 0 0 |
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End of preview. Expand
in Data Studio
This dataset was created using LeRobot.
Dataset Description
Repository: X-VLA
License: Apache 2.0
Paper: Zheng et al., 2025, “X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model” (arXiv:2510.10274)
Dataset Structure
{
"codebase_version": "v3.0",
"robot_type": "franka",
"total_episodes": 1542,
"total_frames": 2852512,
"total_tasks": 1,
"chunks_size": 1000,
"data_files_size_in_mb": 100,
"video_files_size_in_mb": 500,
"fps": 20,
"splits": {
"train": "0:1542"
},
"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": {
"observation.images.cam_high": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"rgb"
],
"info": {
"video.height": 480,
"video.width": 640,
"video.codec": "av1",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 20,
"video.channels": 3,
"has_audio": false
}
},
"observation.images.cam_left_wrist": {
"dtype": "video",
"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"rgb"
],
"info": {
"video.height": 480,
"video.width": 640,
"video.codec": "av1",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 20,
"video.channels": 3,
"has_audio": false
}
},
"observation.images.cam_right_wrist": {
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"shape": [
480,
640,
3
],
"names": [
"height",
"width",
"rgb"
],
"info": {
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"video.width": 640,
"video.codec": "av1",
"video.pix_fmt": "yuv420p",
"video.is_depth_map": false,
"video.fps": 20,
"video.channels": 3,
"has_audio": false
}
},
"observation.state": {
"dtype": "float32",
"shape": [
96
],
"names": [
"eef_euler_0",
"eef_euler_1",
"eef_euler_2",
"eef_euler_3",
"eef_euler_4",
"eef_euler_5",
"eef_euler_6",
"eef_euler_7",
"eef_euler_8",
"eef_euler_9",
"eef_euler_10",
"eef_euler_11",
"eef_euler_12",
"eef_euler_13",
"eef_quat_0",
"eef_quat_1",
"eef_quat_2",
"eef_quat_3",
"eef_quat_4",
"eef_quat_5",
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"eef_quat_15",
"eef6d_0",
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"eef6d_2",
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"eef6d_4",
"eef6d_5",
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"eef6d_8",
"eef6d_9",
"eef6d_10",
"eef6d_11",
"eef6d_12",
"eef6d_13",
"eef6d_14",
"eef6d_15",
"eef6d_16",
"eef6d_17",
"eef6d_18",
"eef6d_19",
"eef_left_time",
"eef_right_time",
"qpos_0",
"qpos_1",
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"qvel_5",
"qvel_6",
"qvel_7",
"qvel_8",
"qvel_9",
"qvel_10",
"qvel_11",
"qvel_12",
"qvel_13",
"effort_0",
"effort_1",
"effort_2",
"effort_3",
"effort_4",
"effort_5",
"effort_6",
"effort_7",
"effort_8",
"effort_9",
"effort_10",
"effort_11",
"effort_12",
"effort_13",
"qpos_left_time",
"qpos_right_time"
]
},
"action": {
"dtype": "float32",
"shape": [
14
],
"names": {
"motors": [
"joint_action_0",
"joint_action_1",
"joint_action_2",
"joint_action_3",
"joint_action_4",
"joint_action_5",
"joint_action_6",
"joint_action_7",
"joint_action_8",
"joint_action_9",
"joint_action_10",
"joint_action_11",
"joint_action_12",
"joint_action_13"
]
}
},
"time_stamp": {
"dtype": "float32",
"shape": [
1
],
"names": {
"values": [
"global_timestamp"
]
}
},
"timestamp": {
"dtype": "float32",
"shape": [
1
],
"names": null
},
"frame_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"episode_index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"index": {
"dtype": "int64",
"shape": [
1
],
"names": null
},
"task_index": {
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"shape": [
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],
"names": null
}
}
}
Note
The action labels in this dataset have an issue: the left- and right-arm actions are not perfectly synchronized. We recommend re-interpolating them using the provided timestamps. Please refer to our official code for the guidance
Citation
If you find this dataset helpful to your project, please kindly cite us
BibTeX:
@article{zheng2025x,
title = {X-VLA: Soft-Prompted Transformer as Scalable Cross-Embodiment Vision-Language-Action Model},
author = {Zheng, Jinliang and Li, Jianxiong and Wang, Zhihao and Liu, Dongxiu and Kang, Xirui
and Feng, Yuchun and Zheng, Yinan and Zou, Jiayin and Chen, Yilun and Zeng, Jia and others},
journal = {arXiv preprint arXiv:2510.10274},
year = {2025}
}
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Size of downloaded dataset files:
801 MB
Size of the auto-converted Parquet files:
801 MB
Number of rows:
2,852,512