156 citations · 342 across the 14 of their papers we have counts for
5 papers · 1 filter
Multi-Modal Knowledge Graph Transformer Framework for Multi-Modal Entity Alignment
Qian Li, Cheng Ji, Shu Guo +3
Multi-Modal Entity Alignment (MMEA) is a critical task that aims to identify equivalent entity pairs across multi-modal knowledge graphs (MMKGs). However, this task faces challenge…
Dual-Gated Fusion with Prefix-Tuning for Multi-Modal Relation Extraction
Qian Li, Shu Guo, Cheng Ji +3
Multi-Modal Relation Extraction (MMRE) aims at identifying the relation between two entities in texts that contain visual clues. Rich visual content is valuable for the MMRE task,…
Attribute-Consistent Knowledge Graph Representation Learning for Multi-Modal Entity Alignment
Qian Li, Shu Guo, Yangyifei Luo +4
The multi-modal entity alignment (MMEA) aims to find all equivalent entity pairs between multi-modal knowledge graphs (MMKGs). Rich attributes and neighboring entities are valuable…
A Comprehensive Survey on Automatic Knowledge Graph Construction
Lingfeng Zhong, Jia Wu, Qian Li +2
Automatic knowledge graph construction aims to manufacture structured human knowledge. To this end, much effort has historically been spent extracting informative fact patterns fro…
A Comprehensive Survey on Pretrained Foundation Models: A History from BERT to ChatGPT
Ce Zhou, Qian Li, Chen Li +16
Pretrained Foundation Models (PFMs) are regarded as the foundation for various downstream tasks with different data modalities. A PFM (e.g., BERT, ChatGPT, and GPT-4) is trained on…