spikefly/SemanticVLA-TraceX-240K-Bridge

SemanticVLA TraceX 240K · Bridge

🎉 Accepted to CVPR 2026.
✍️ Fei Ni¹, Zhuo Chen², Yifu Yuan³, Zibin Dong³, Xianze Yao³, Shan Luo², Jianye Hao³, Jiankang Deng¹†, Stefanos Zafeiriou¹†
🏫 ¹Imperial College London    ²King's College London    ³Tianjin University
✉️ Primary contact: f.ni@imperial.ac.uk

The Bridge component of TraceX-240K — the trace-annotated trajectory corpus introduced in SemanticVLA. This package is a LeRobot v3.0 repack of BridgeData V2 · WidowX with dense per-frame end-effector trace labels stored directly in every frame row.

📚 Code · checkpoints · paper: https://github.com/Fei-Ni/SemanticVLA_Offcial

🎬 Sample trace overlays

Each clip shows the orange trace label (per-frame gripper position) overlaid on the original episode camera feed.

episode 5317	episode 10663	episode 21302	episode 15995

🧭 Trace label schema

Dense per-frame end-effector position columns, stored directly in every frame row:

• trace.x — float32[1], normalized image-space x coordinate on a [0, 100] scale.
• trace.y — float32[1], normalized image-space y coordinate on a [0, 100] scale.

(0, 0) is the top-left corner of the frame, (100, 100) the bottom-right.

📦 Contents

Field	Value
HF repo	spikefly/SemanticVLA-TraceX-240K-Bridge
Format	LeRobot v3.0
Episodes	53,192
Frames	1,999,410
FPS	5
Robot type	widowx
Source dataset	BridgeData V2 (v1.0.0)
Data file target	100 MB
Video file target	500 MB

Video streams

• observation.images.image_0
• observation.images.image_1
• observation.images.image_2
• observation.images.image_3

📂 Sibling datasets in TraceX-240K

Dataset	HF Repository	Embodiment
Fractal	spikefly/SemanticVLA-TraceX-240K-Fractal	Fractal / Google Robot (RT-1)
BC-Z	spikefly/SemanticVLA-TraceX-240K-BC-Z	BC-Z / Google Robot
DROID	spikefly/SemanticVLA-TraceX-240K-DROID	DROID / Franka

✏️ Citation

If you use this dataset, please cite SemanticVLA:

@inproceedings{ni2026semanticvla,
  title     = {SemanticVLA: Towards Semantic Reasoning over Action Memorization via Synergistic Explicit Trace and Latent Action Planning},
  author    = {Ni, Fei and Chen, Zhuo and Yuan, Yifu and Dong, Zibin and Yao, Xianze and Luo, Shan and Hao, Jianye and Deng, Jiankang and Zafeiriou, Stefanos},
  booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year      = {2026}
}

📜 License & terms

The trace annotation labels (trace.x / trace.y) are released under the MIT License as part of the SemanticVLA code release. Use of the underlying robot trajectory data is subject to the original source dataset terms (BridgeData V2 (v1.0.0)). Please consult the upstream dataset license before use.