README.md

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pipeline_tag: image-text-to-text
---

# SPLASH-1B: Wake up for Touch! Mask-isolated Tactile Alignment Learning in MLLMs

This repository contains the SPLASH-1B model checkpoint presented in the paper [Wake up for Touch! Mask-isolated Tactile Alignment Learning in MLLMs](https://huggingface.co/papers/2607.00302).

SPLASH-1B integrates tactile perception into vision-language models by using [InternVL2.5-1B](https://huggingface.co/OpenGVLab/InternVL2_5-1B) as the base MLLM backbone and a ViT-Tiny tactile frontend.

- **Project Page:** [https://ewha-mmai.github.io/splash/](https://ewha-mmai.github.io/splash/)
- **Repository:** [https://github.com/ewha-mmai/splash](https://github.com/ewha-mmai/splash)

## Description

SPLASH integrates tactile perception into vision-language models through a two-stage pipeline:
1. **Dormant Mask Generation:** Quantifies the significance of each pretrained parameter via weight & activation importance scoring on the LLM backbone, partitioning the parameter space into a dormant and critical subspace.
2. **Mask-Guided Sparse Training:** Updates the isolated dormant subspace to align tactile representations while freezing the critical subspace to safeguard established vision-language reasoning, preventing catastrophic forgetting.

<p align="center">
  <img src="https://raw.githubusercontent.com/ewha-mmai/splash/main/assets/figure.png" width="100%">
</p>

## Citation

If you find SPLASH useful, please cite the paper:

```bibtex
@inproceedings{park2026splash,
  title={Wake up for Touch! Mask-isolated Tactile Alignment Learning in MLLMs},
  author={Yoonhyung Park and Minji Kim and Sungwon Moon and Jiyoung Lee},
  booktitle={European Conference on Computer Vision (ECCV)},
  year={2026}
}
```