F2IND-IT! -- Multimodal Fuzzy Fake Indian News Detection using Images and Text
Biased manipulation of facts across regional and national media outlets complicates misinformation detection in diverse landscapes like India. This paper introduces a novel multimodal framework combining visual and textual modalities for enhanced fake news detection on Indian media. The architecture utilizes a ResNet-50 Convolutional Neural Network to extract visual features from news images, a DistilBERT encoder to obtain textual semantic embeddings, and an Adaptive Neuro-Fuzzy Inference System (ANFIS) to generate a fuzzy reliability score. A lightweight attention-based fusion module assigns learnable weights to each modality prior to classification. Evaluated on the IFND dataset, the pr...
| Authors | Kushal Trivedi, Murtuza Shaikh, Khushi Singh et al. |
|---|---|
| Primary category | cs.AI |
| Published | 16 May 2026 |
| Last updated at source | 16 May 2026 |
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