K3M
K3M
**K3M** is a multi-modal pretraining method for e-commerce product data that introduces knowledge modality to correct the noise and supplement the missing of image and text modalities. The modal-encoding layer extracts the features of each modality. The modal-interaction layer is capable of effectively modeling the interaction of multiple modalities, where an initial-interactive feature fusion model is designed to maintain the independence of image modality and text modality, and a structure aggregation module is designed to fuse the information of image, text, and knowledge modalities. K3M is pre-trained with three pretraining tasks, including masked object modeling (MOM), masked language modeling (MLM), and link prediction modeling ([LPM](https://paperswithcode.com/method/local-prior-matching)).
Knowledge Perceived Multi-modal Pretraining in E-commerce
https://paperswithcode.com/paper/knowledge-perceived-multi-modal-pretraining
Knowledge Perceived Multi-modal Pretraining in E-commerce