26 citations · 68 across the 8 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…
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…
Type Information Utilized Event Detection via Multi-Channel GNNs in Electrical Power Systems
Qian Li, Jianxin Li, Lihong Wang +6
Event detection in power systems aims to identify triggers and event types, which helps relevant personnel respond to emergencies promptly and facilitates the optimization of power…
CasEE: A Joint Learning Framework with Cascade Decoding for Overlapping Event Extraction
Jiawei Sheng, Shu Guo, Bowen Yu +5
Event extraction (EE) is a crucial information extraction task that aims to extract event information in texts. Most existing methods assume that events appear in sentences without…
Adaptive Attentional Network for Few-Shot Knowledge Graph Completion
Jiawei Sheng, Shu Guo, Zhenyu Chen +4
Few-shot Knowledge Graph (KG) completion is a focus of current research, where each task aims at querying unseen facts of a relation given its few-shot reference entity pairs. Rece…