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cs.LG2026
The Chicken and Egg Dilemma: Co-optimizing Data and Model Configurations for LLMs
Zhiliang Chen, Alfred Wei Lun Leong, Shao Yong Ong +6
Co-optimizing data and model configurations for training LLMs presents a classic chicken-and-egg dilemma: The best training data configuration (e.g., data mixture) for a downstream…
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…