README.md

---
license: apache-2.0
task_categories:
- robotics
- keypoint-detection
tags:
- robot-manipulation
- vision-language-models
- zero-shot-generalization
- bridge-v2
---

# PEEK VLM-Labeled BRIDGE_v2 dataset

This dataset contains the LeRobot-format BRIDGE-v2 dataset with paths and masks from the PEEK VLM drawn onto the image: [PEEK: Guiding and Minimal Image Representations for Zero-Shot Generalization of Robot Manipulation Policies](https://huggingface.co/papers/2509.18282).

PEEK fine-tunes Vision-Language Models (VLMs) to predict a unified point-based intermediate representation for robot manipulation. This representation consists of:
1.  **End-effector paths:** specifying what actions to take.
2.  **Task-relevant masks:** indicating where to focus.

These annotations are directly overlaid onto robot observations, making the representation policy-agnostic and transferable across architectures. This dataset provides these automatically generated labels for the BRIDGE_v2 dataset, enabling researchers to readily use them for policy training and enhancement to boost zero-shot generalization.

## Paper
[PEEK: Guiding and Minimal Image Representations for Zero-Shot Generalization of Robot Manipulation Policies](https://huggingface.co/papers/2509.18282)

## Project Page
[https://peek-robot.github.io](https://peek-robot.github.io/)

## Code/Github Repository
The main PEEK framework and associated code can be found on the Github repository:
[https://github.com/peek-robot/peek](https://github.com/peek-robot/peek)

## Sample Usage
This dataset provides the BRIDGE_v2 dataset labeled with PEEK VLM path and mask labels.

## Citation

If you find this dataset useful for your research, please cite the original paper:

```bibtex
@inproceedings{zhang2025peek,
    title={PEEK: Guiding and Minimal Image Representations for Zero-Shot Generalization of Robot Manipulation Policies}, 
    author={Jesse Zhang and Marius Memmel and Kevin Kim and Dieter Fox and Jesse Thomason and Fabio Ramos and Erdem Bıyık and Abhishek Gupta and Anqi Li},
    booktitle={arXiv:2509.18282},
    year={2025},
}
```