12 citations · 13 across the 10 of their papers we have counts for
11 papers
Damage-TriageFormer: A Foundation-Model Framework for Typology-Based Building Damage Assessment from Mono-Temporal Imagery
Yiming Xiao, Yu-Hsuan Ho, Sanjay Thasma +2
Decision-relevant building damage assessment is critical for prioritizing resources and recovery after a disaster, yet most automated methods either flatten damage into a single se…
DisasterLex: An Expert Concept-to-Schema Knowledge Graph for Geospatial Reasoning in Disaster Analytics
Yiming Xiao, Ankit Basu, Kai Yin +3
Disasters are inevitable and increasingly costly, and effective response depends on querying structured tabular data: precise, information-dense records of hazard, exposure, vulner…
DisasterBench: Benchmarking LLM Planning under Typed Tool Interface Constraints
Zhitong Chen, Kai Yin, Weifeng Zhang +7
Disasters cause severe societal impacts, demanding rapid coordination of heterogeneous AI tools, from satellite analysis to flood prediction and damage assessment, into coherent mu…
DisastRAG: A Multi-Source Disaster Information Integration and Access System Based on Retrieval-Augmented Large Language Models
Bo Li, Zhitong Chen, Kai Yin +3
Effective disaster management requires rapid access to information distributed across structured operational records, unstructured institutional documents, and dynamic external sou…
Automating UI Optimization through Multi-Agentic Reasoning
Zhipeng Li, Christoph Gebhardt, Yi-Chi Liao +1
We present AutoOptimization, a novel multi-objective optimization framework for adapting user interfaces. From a user's verbal preferences for changing a UI, our framework guides a…
DisastQA: A Comprehensive Benchmark for Evaluating Question Answering in Disaster Management
Zhitong Chen, Kai Yin, Xiangjue Dong +7
Accurate question answering (QA) in disaster management requires reasoning over uncertain and conflicting information, a setting poorly captured by existing benchmarks built on cle…
Disaster Management in the Era of Agentic AI Systems: A Vision for Collective Human-Machine Intelligence for Augmented Resilience
Bo Li, Junwei Ma, Kai Yin +3
The escalating frequency and severity of disasters routinely overwhelm traditional response capabilities, exposing critical vulnerability in disaster management. Current practices…
Recov-Vision: Linking Street View Imagery and Vision-Language Models for Post-Disaster Recovery
Yiming Xiao, Archit Gupta, Miguel Esparza +5
Building-level occupancy after disasters is vital for triage, inspections, utility re-energization, and equitable resource allocation. Overhead imagery provides rapid coverage but…
Automated Wildfire Damage Assessment from Multi view Ground level Imagery Via Vision Language Models
Miguel Esparza, Archit Gupta, Kai Yin +2
The escalating intensity and frequency of wildfires demand innovative computational methods for rapid and accurate property damage assessment. Traditional methods are often time-co…
DisastIR: A Comprehensive Information Retrieval Benchmark for Disaster Management
Kai Yin, Xiangjue Dong, Chengkai Liu +5
Effective disaster management requires timely access to accurate and contextually relevant information. Existing Information Retrieval (IR) benchmarks, however, focus primarily on…
DamageCAT: A Deep Learning Transformer Framework for Typology-Based Post-Disaster Building Damage Categorization
Yiming Xiao, Ali Mostafavi
Rapid, accurate, and descriptive building damage assessment is critical for directing post-disaster resources, yet current automated methods typically provide only binary (damaged/…