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cs.LG2025
Co-LoRA: Collaborative Model Personalization on Heterogeneous Multi-Modal Clients
Minhyuk Seo, Taeheon Kim, Hankook Lee +2
As AI becomes more personal, e.g., Agentic AI, there is an increasing need for personalizing models for various use cases. Personalized federated learning (PFL) enables each client…
cs.LG2025
Representation Bending for Large Language Model Safety
Ashkan Yousefpour, Taeheon Kim, Ryan S. Kwon +7
Large Language Models (LLMs) have emerged as powerful tools, but their inherent safety risks - ranging from harmful content generation to broader societal harms - pose significant…
cs.LG2024
An Information Theoretic Evaluation Metric For Strong Unlearning
Dongjae Jeon, Wonje Jeung, Taeheon Kim +2
Machine unlearning (MU) aims to remove the influence of specific data from trained models, addressing privacy concerns and ensuring compliance with regulations such as the ``right…