3 papers
cs.AI2026
The Reward Model Selection Crisis in Personalized Alignment
Fady Rezk, Yuangang Pan, Chuan-Sheng Foo +4
Personalized alignment from preference data has focused primarily on improving personal reward model (RM) accuracy, with the implicit assumption that better preference ranking tran…
cs.LG2025
Model Diffusion for Certifiable Few-shot Transfer Learning
Fady Rezk, Royson Lee, Henry Gouk +2
In contemporary deep learning, a prevalent and effective workflow for solving low-data problems is adapting powerful pre-trained foundation models (FMs) to new tasks via parameter-…
cs.CL2025
FedPEFT: Federated Learning to Personalize PEFT for Multilingual LLMs
Royson Lee, Minyoung Kim, Fady Rezk +3
Federated learning (FL) has enabled the training of multilingual large language models (LLMs) on diverse and decentralized multilingual data, especially on low-resource languages.…