activity
20182026
most citedLearning to Exploit Long-term Relational Dependencies in Knowledge Graphs

106 citations · 221 across the 33 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.CL2023★ 2 cited

Universal Multi-modal Entity Alignment via Iteratively Fusing Modality Similarity Paths

Bolin Zhu, Xiaoze Liu, Xin Mao +4

The objective of Entity Alignment (EA) is to identify equivalent entity pairs from multiple Knowledge Graphs (KGs) and create a more comprehensive and unified KG. The majority of E…

cs.AI2023★ 2 cited

Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment

Zhuo Chen, Lingbing Guo, Yin Fang +6

As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to identify identical entities across disparate knowledge graphs (KGs) by exploiting assoc…

cs.CL2023★ 3 cited

Revisit and Outstrip Entity Alignment: A Perspective of Generative Models

Lingbing Guo, Zhuo Chen, Jiaoyan Chen +3

Recent embedding-based methods have achieved great successes in exploiting entity alignment from knowledge graph (KG) embeddings of multiple modalities. In this paper, we study emb…

cs.LG2023★ 2 cited

Newton-Cotes Graph Neural Networks: On the Time Evolution of Dynamic Systems

Lingbing Guo, Weiqing Wang, Zhuo Chen +5

Reasoning system dynamics is one of the most important analytical approaches for many scientific studies. With the initial state of a system as input, the recent graph neural netwo…

cs.LG2023★ 17 cited

Domain-Agnostic Molecular Generation with Chemical Feedback

Yin Fang, Ningyu Zhang, Zhuo Chen +3

The generation of molecules with desired properties has become increasingly popular, revolutionizing the way scientists design molecular structures and providing valuable support f…