Yi Zeng

DiverValue-Bench: A Benchmark and Fine-Tuning Framework for Aligning Large Language Models with Diverse Human Values

DiverValue-Bench is introduced, a population-aware benchmark for evaluating multi-dimensional value alignment across 74 countries/regions and it is shown that lightweight preference-based fine-tuning with Low-Rank Adaptation and Direct Preference Optimization substantially improves in-domain value alignment while yielding consistent out-of-domain gains.