DisastIR: A Comprehensive Information Retrieval Benchmark for Disaster Management (2025.findings-emnlp)
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Kai Yin, Xiangjue Dong, Chengkai Liu, Lipai Huang, Yiming Xiao, Zhewei Liu, Ali Mostafavi, James Caverlee
| Challenge: | Existing information retrieval benchmarks focus on general or specialized domains, such as medicine or finance, neglecting the unique linguistic complexity and diverse information needs encountered in disaster management scenarios. |
| Approach: | DisastIR is the first comprehensive IR evaluation benchmark specifically tailored for disaster management. |
| Outcome: | DisastIR covers 48 retrieval tasks derived from six search intents and eight general disaster categories . evaluations show no single model excelling universally . |
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