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This paper evaluates multimodal LLMs for disaster risk communication, finding that current models lack consistency across text and audio modalities, which undermines accessibility for vulnerable populations.
This paper reviews recent advances in using natural language processing and large language models to extract socio-economic impact data from text sources for climate hazards, identifies key challenges, and provides recommendations for robust dataset construction.