DisImpact introduces a two-stage MLLM framework to classify disaster-related social media posts into ten impact categories and compute a unified physi-social impact index validated against FEMA and NASA ground-truth data.
arXiv preprint arXiv:2501.17880 , year=
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 3verdicts
UNVERDICTED 3roles
background 1polarities
background 1representative citing papers
An MDP framework with approximate dynamic programming optimizes power line switching during wildfires to minimize costs under decision-dependent uncertainty, tested on 54-bus and 138-bus systems.
The authors introduce a validation framework showing LLMs can pull causal links from disaster social media but require checks against post-event evidence to avoid relying on model priors.
citing papers explorer
-
DisImpact: Quantifying the Physi-Social Impact of Natural Disasters Through Social Media
DisImpact introduces a two-stage MLLM framework to classify disaster-related social media posts into ten impact categories and compute a unified physi-social impact index validated against FEMA and NASA ground-truth data.
-
A Markov Decision Process Framework for Enhancing Power System Resilience during Wildfires under Decision-Dependent Uncertainty
An MDP framework with approximate dynamic programming optimizes power line switching during wildfires to minimize costs under decision-dependent uncertainty, tested on 54-bus and 138-bus systems.
-
Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence
The authors introduce a validation framework showing LLMs can pull causal links from disaster social media but require checks against post-event evidence to avoid relying on model priors.