FairNet: Dynamic Fairness Correction without Performance Loss via Contrastive Conditional LoRA

Songqi Zhou, Zeyuan Liu, Benben Jiang

Ensuring fairness in machine learning models is a critical challenge. Existing debiasing methods often compromise performance, rely on static correction strategies, and struggle wi…