Awesome
MultiDelete for Multimodal Machine Unlearning
Authors:
MultiDelete Paper: ECCV 2024, Preprint
Overview
We propose MultiDelete, the first machine unlearning method that targets unlearning multimodal data and models (MLLM). It formulates multimodal unlearning as 1) Modality Decoupling, 2) Multimodal Knowledge Retention, 3) Unimodal Knowledge Retention.
<p align="center"> <img src="images/fig1.png" width="1000" align="center"> </p>How to run
- Step 1. Train original model
bash bash/ori.sh
- Step 2. Unlearn
python bash/run.py
Citation
If you find MultiDelete useful for your research, please consider citing this paper:
@inproceedings{cheng2024multidelete,
author="Cheng, Jiali
and Amiri, Hadi",
title="MultiDelete for Multimodal Machine Unlearning",
booktitle="Computer Vision -- ECCV 2024",
year="2025",
publisher="Springer Nature Switzerland",
isbn="978-3-031-72940-9"
}