7 citations · 9 across the 15 of their papers we have counts for
18 papers
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…
Cognitively Layered Data Synthesis for Domain Adaptation of LLMs to Space Situational Awareness
Ding Linghu, Cheng Wang, Da Fan +6
Large language models (LLMs) demonstrate exceptional performance on general-purpose tasks. however, transferring them to complex engineering domains such as space situational aware…
Training-free retrieval-augmented generation with reinforced reasoning for flood damage nowcasting
Lipai Huang, Kai Yin, Chia-Fu Liu +1
We propose R2RAG-Flood, a training-free retrieval-augmented generation framework for flood damage nowcasting with reinforced reasoning. The framework builds a reasoning-centric kno…
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…
FloodSQL-Bench: A Retrieval-Augmented Benchmark for Geospatially-Grounded Text-to-SQL
Hanzhou Liu, Kai Yin, Zhitong Chen +2
Existing Text-to-SQL benchmarks primarily focus on single-table queries or limited joins in general-purpose domains, and thus fail to reflect the complexity of domain-specific, mul…
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…
DMRetriever: A Family of Models for Improved Text Retrieval in Disaster Management
Kai Yin, Xiangjue Dong, Chengkai Liu +4
Effective and efficient access to relevant information is essential for disaster management. However, no retrieval model is specialized for disaster management, and existing genera…
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…
CrisisSense-LLM: Instruction Fine-Tuned Large Language Model for Multi-label Social Media Text Classification in Disaster Informatics
Kai Yin, Bo Li, Chengkai Liu +2
In the field of crisis/disaster informatics, social media is increasingly being used for improving situational awareness to inform response and relief efforts. Efficient and accura…
FloodDamageCast: Building Flood Damage Nowcasting with Machine Learning and Data Augmentation
Chia-Fu Liu, Lipai Huang, Kai Yin +2
Near-real time estimation of damage to buildings and infrastructure, referred to as damage nowcasting in this study, is crucial for empowering emergency responders to make informed…
Rethinking Urban Flood Risk Assessment By Adapting Health Domain Perspective
Zhewei Liu, Kai Yin, Ali Mostafavi
Inspired by ideas from health risk assessment, this paper presents a new perspective for flood risk assessment. The proposed perspective focuses on three pillars for examining floo…
Deep Learning-driven Community Resilience Rating based on Intertwined Socio-Technical Systems Features
Kai Yin, Bo Li, Ali Mostafavi
Community resilience is a complex and muti-faceted phenomenon that emerges from complex and nonlinear interactions among different socio-technical systems and their resilience prop…
Unsupervised Graph Deep Learning Reveals Emergent Flood Risk Profile of Urban Areas
Kai Yin, Junwei Ma, Ali Mostafavi
Urban flood risk emerges from complex and nonlinear interactions among multiple features related to flood hazard, flood exposure, and social and physical vulnerabilities, along wit…
Characterizing Community Formation in Response to Extreme Weather Events through Human Mobility Networks
Cheng-Chun Lee, Junwei Ma, Kai Yin +3
Community formation in socio-spatial human networks is one of the important mechanisms for mitigating hazard impacts of extreme weather events. Research is scarce regarding latent…