Multimodal LDA topic model

Multimodal LDA extends Latent Dirichlet Allocation to jointly model multiple data modalities — most often text and images — within a single probabilistic topic framework. Each document or data instance is represented as a mixture of latent topics shared across modalities, enabling the model to discover coherent themes that align visual and linguistic content simultaneously.