URMF: Uncertainty-aware Robust Multimodal Fusion for Multimodal Sarcasm Detection
Multimodal sarcasm detection (MSD) aims to identify sarcastic intent from semantic incongruity between text and image. Although recent methods have improved MSD through cross-modal interaction and incongruity reasoning, most still treat modalities as equally reliable. In real social media posts, however, text and images often differ in noise level and relevance, making deterministic fusion susceptible to noisy evidence and weakened incongruity cues. To address this issue, we propose Uncertainty-aware Robust Multimodal Fusion (URMF), a unified framework for robust MSD. URMF first injects visual evidence into textual representations through multi-head cross-attention, and then applies self-...
| Authors | Zhenyu Wang, Weichen Cheng, Weijia Li et al. |
|---|---|
| Primary category | cs.CV |
| Published | 8 April 2026 |
| Last updated at source | 3 May 2026 |
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