6 papers
Large Language Models for Causal Relations Extraction in Social Media: A Validation Framework for Disaster Intelligence
Ujun Jeong, Saketh Vishnubhatla, Bohan Jiang +3
During disasters, extracting causal relations from social media can strengthen situational awareness by identifying factors linked to casualties, physical damage, infrastructure di…
DAGverse: Building Document-Grounded Semantic DAGs from Scientific Papers
Shu Wan, Saketh Vishnubhatla, Iskander Kushbay +4
Directed Acyclic Graphs (DAGs) are widely used to represent structured knowledge in scientific and technical domains. However, datasets for real-world DAGs remain scarce because co…
Proxy-Guided Measurement Calibration
Saketh Vishnubhatla, Shu Wan, Andre Harrison +2
Aggregate outcome variables collected through surveys and administrative records are often subject to systematic measurement error. For instance, in disaster loss databases, county…
CAMO: Causality-Guided Adversarial Multimodal Domain Generalization for Crisis Classification
Pingchuan Ma, Chengshuai Zhao, Bohan Jiang +5
Crisis classification in social media aims to extract actionable disaster-related information from multimodal posts, which is a crucial task for enhancing situational awareness and…
An Interventional Approach to Real-Time Disaster Assessment via Causal Attribution
Saketh Vishnubhatla, Alimohammad Beigi, Rui Heng Foo +5
Traditional disaster analysis and modelling tools for assessing the severity of a disaster are predictive in nature. Based on the past observational data, these tools prescribe how…
Assessing On-the-Ground Disaster Impact Using Online Data Sources
Saketh Vishnubhatla, Ujun Jeong, Bohan Jiang +4
Assessing the impact of a disaster in terms of asset losses and human casualties is essential for preparing effective response plans. Traditional methods include offline assessment…