Zhaoji Liang — accepted AI-conference papers

2026

Multi-Modal Fact Knowledge Generation for Imbalanced Cross-Source Entity Alignment

Qian Li, Cheng Ji, Zhaoji Liang, Yuzheng Zhang, Zhuo Chen, Siyuan Liang

AAAI 2026technical

Multi-modal imbalanced cross-source entity alignment aims to identify equivalent entity pairs across multi-modal knowledge graphs (MMKGs) that encompass diverse data sources with imbalanced modality, which poses significant challenges due to the non-uniform distribution of information across differe

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2023

Multi-Modal Knowledge Graph Transformer Framework for Multi-Modal Entity Alignment

Qian Li, Cheng Ji, Shu Guo, Zhaoji Liang, Lihong Wang, Jianxin Li

EMNLP 2023long findings

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 challenges due to the presence of different types of information, including neighboring entities, multi-modal attributes, and ent…

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