3 citations · 3 across the 3 of their papers we have counts for
4 papers
MGDT: MLLM-Guided Diffusion Transformer with Relation-Adaptive Mixture-of-Experts for Multimodal Knowledge Graph Completion
Xu Hou, Meiyu Liang, Wei Huang +6
Multimodal Knowledge Graph Completion (MKGC) requires inferring missing entities from structural, textual, and visual cues. Existing diffusion-based MKGC methods usually denoise di…
ELMM: Efficient Lightweight Multimodal Large Language Models for Multimodal Knowledge Graph Completion
Wei Huang, Peining Li, Meiyu Liang +7
Multimodal Knowledge Graphs (MKGs) extend traditional knowledge graphs by incorporating visual and textual modalities, enabling richer and more expressive entity representations. H…
DiffusionCom: Structure-Aware Multimodal Diffusion Model for Multimodal Knowledge Graph Completion
Wei Huang, Meiyu Liang, Peining Li +5
Most current MKGC approaches are predominantly based on discriminative models that maximize conditional likelihood. These approaches struggle to efficiently capture the complex con…
Dynamic Self-adaptive Multiscale Distillation from Pre-trained Multimodal Large Model for Efficient Cross-modal Representation Learning
Zhengyang Liang, Meiyu Liang, Wei Huang +2
In recent years, pre-trained multimodal large models have attracted widespread attention due to their outstanding performance in various multimodal applications. Nonetheless, the e…