Abstract
Aligning pretrained language models (LMs) often requires large-scale preference data and substantial computational resources. These costs become even more prohibitive for multi-objective or pluralistic alignment. Is this truly necessary? Can we perform efficient alignment using only internal model capabilities, and without additional training? To answer this question, we propose AlignEZ, a novel a