Papers by Zhongzheng Qiao

1 papers
CrisisTS: Coupling Social Media Textual Data and Meteorological Time Series for Urgency Classification (2025.acl-long)

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Challenge: Existing studies on fusion of texts and tabular-based time series to improve performance of NLP applications have focused on coupling texts with tabular time series.
Approach: They propose a multimodal and multilingual dataset for urgency classification that allows for temporal and location alignment even in the absence of location mention in the text.
Outcome: The proposed dataset outperforms text-only models in many applications while ensuring model generalizability.

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