arXiv Computation and Language
GeoSense-AI: Fast Location Inference from Crisis Microblogs
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DisasterTD: Disaster Toponym Disambiguation Using Multimodal LLMs and Cross-View Geolocalization
arXiv:2607. 24856v1 Announce Type: cross Abstract: Social media imagery (SMI) provides timely and fine-grained ground perspectives that are valuable for situational awareness and emergency response.
Hugging Face Trending Papers
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HUMAID-NER: A Disaster Tweet Dataset for Joint Named Entity Recognition and Event Classification via Uncertainty-Weighted Multitask Learning
Rapid extraction of structured information from social media is important for humanitarian response, yet existing disaster tweet resources mainly provide document-level category labels without span-le...
arXiv Machine Learning
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HUMAID-NER: A Disaster Tweet Dataset for Joint Named Entity Recognition and Event Classification via Uncertainty-Weighted Multitask Learning
HUMAID-NER is the first named entity recognition dataset built on the HumAID benchmark, comprising 60,000 English disaster tweets with approximately 175,000 labeled entity spans across ten operationally motivated entity types. The dataset was created using a reproducible three‑stage hybrid pipeline that combines a spaCy transformer model, disaster‑domain EntityRuler patterns, and structured regular expressions with priority‑based overlap resolution. A joint multitask learning framework using a shared RoBERTa‑large encoder and homoscedastic uncertainty weighting achieves an NER span micro‑F1 of 0.841 and classification macro‑F1 of 0.761, and the authors provide a real‑time web dashboard, dataset, models, and pipeline code for reproducibility.
arXiv Computation and Language
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CrisisFake: Benchmark Validity of AI-Generated Text Detection for Disaster Social Sensing
arXiv:2609.35821v2 Announce Type: replace Abstract: Disaster social sensing converts public social-media posts into evidence for situational awareness and humanitarian response, but plausible LLM-gen...
arXiv AI
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A Decade of PhotoMappers: A Longitudinal Study of Crowdsourced Disaster Photos Geolocalization with Vision-Language Models and Geospatial Reasoning
arXiv:2610.15403v1 Announce Type: new Abstract: Crowdsourced disaster imagery provides timely, ground-level observations when conventional disaster mapping is delayed or incomplete, yet its geographi...
Hugging Face Trending Papers
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Guide Me Out: A Framework to Benchmark VLM Operators Communication in Crisis Scenarios
Effective crisis response requires spatially grounded communication that bridges linguistic guidance of civilians with the physical environment, accounting for structural bottlenecks, evolving threats, and agent-specific contexts. Yet, current NLP research in crisis communication remains mainly limited to static, text-only classification settings, overlooking the critical communicative role of AI operators in dynamic, embodied scenarios.