4 papers
AutoAnchor: Stable Diffusion Unlearning Using Cross-Attention as a Manifold Surrogate
Siyuan Wen, Jiahao Zeng, Ningning Ding
Diffusion unlearning is essential for mitigating the generation of harmful or copyrighted content in text-to-image models. Current diffusion unlearning techniques determine the mod…
Learning to Route LLMs from Implicit Cost-Performance Preferences via Meta-Learning
Jiahao Zeng, Ming Tang, Ningning Ding
Large language models (LLMs) present a trade-off between performance and cost, where more powerful models incur greater expense. LLM routing aims to mitigate expenses while maintai…
CiPO: Counterfactual Unlearning for Large Reasoning Models through Iterative Preference Optimization
Junyi Li, Yongqiang Chen, Ningning Ding
Machine unlearning has gained increasing attention in recent years, as a promising technique to selectively remove unwanted privacy or copyrighted information from Large Language M…
Strategic Data Revocation in Federated Unlearning
Ningning Ding, Ermin Wei, Randall Berry
By allowing users to erase their data's impact on federated learning models, federated unlearning protects users' right to be forgotten and data privacy. Despite a burgeoning body…