Cross-Modal Rationale Transfer for Explainable Humanitarian Classification on Social Media
Advances in social media data dissemination enable the provision of real-time information during a crisis. The information comes from different classes, such as infrastructure damages, persons missing or stranded in the affected zone, etc. Existing methods attempted to classify text and images into various humanitarian categories, but their decision-making process remains largely opaque, which affects their deployment in real-life applications. Recent work has sought to improve transparency by extracting textual rationales from tweets to explain predicted classes. However, such explainable classification methods have mostly focused on text, rather than crisis-related images. In this paper...
| Authors | Thi Huyen Nguyen, Koustav Rudra, Wolfgang Nejdl |
|---|---|
| Primary category | cs.CL |
| Published | 19 March 2026 |
| Last updated at source | 19 March 2026 |
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