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U&ME 2025 @ ICCV 25

The 2nd Workshop and Challenge on Unlearning and Model Editing (U&ME) is a half-day event at ICCV 2025 in Hawaii on October 19-20, 2025, and focuses on the growing need for new, efficient, and effective techniques for editing trained models, especially large generative models. Such models have practically unlimited functionality in the output they can generate. To provide this functionality, generative models require massive amounts of data and enormous compute costs to train, making it prohibitively expensive to retrain them whenever the need arises: when safety risks are uncovered, when deploying them to compute or storage-restricted platforms, or simply due to changing requirements. In particular, ensuring these models are safe and compliant with regulations can be difficult due to their broad range of capabilities and a continuously evolving regulatory landscape.

This workshop provides a venue for original scientific work presenting novel model editing techniques. We also encourage submissions on model compression methods, which aim to minimize the storage and computational costs of operating trained models with little impact on their performance. Additionally, papers that explore methods for adapting foundation models for efficient fine-tuning or editing are relevant.

Workshop topics: We solicit papers on topics including, but not limited to:

Unlearning
Model Stitching and Editing
Model Merging and "MoErging" (Mixture of Experts Merging)
Model compression
Efficient domain adaptation
Multi-domain/cross-domain U&ME
Online/lifelong learning, unlearning, and model editing
Responsible U&ME (e.g., robustness, ethics and fairness, resource efficiency, privacy, and regulatory compliance)
Applications in computer vision

Though we prioritize papers on generative models, but we also welcome submissions that present methods designed for other types of models, such as discriminative classifiers.

News

11 May 2025 - Website created!

21 May 2025 - Updated the details of the Genμ Challenge

1 June 2025 - Challenge Begins! [Details] [Kaggle]

Invited Speakers

Coming soon

Organziers