Yuan-Jun Zhang

Towards reliable multimodal disaster severity assessment through preference optimization and explainable vision-language reasoning

This study proposes a two-stage training framework that integrates Supervised Fine-Tuning (SFT) and Direct Preference Optimization (DPO) within a unified data construction pipeline and provides a reproducible pathway to develop reliable multimodal systems that deliver auditable, actionable disaster insights for emergen...