activity
20192024
most citedKnowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey

31 citations · 104 across the 20 of their papers we have counts for

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Showing 2022Show all

7 papers · 1 filter

cs.AI2022★ 5 cited

MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid

Zhuo Chen, Jiaoyan Chen, Wen Zhang +8

Multi-modal entity alignment (MMEA) aims to discover identical entities across different knowledge graphs (KGs) whose entities are associated with relevant images. However, current…

cs.AI2022★ 1 cited

Tele-Knowledge Pre-training for Fault Analysis

Zhuo Chen, Wen Zhang, Yufeng Huang +14

In this work, we share our experience on tele-knowledge pre-training for fault analysis, a crucial task in telecommunication applications that requires a wide range of knowledge no…

cs.AI2022★ 7 cited

Relational Message Passing for Fully Inductive Knowledge Graph Completion

Yuxia Geng, Jiaoyan Chen, Jeff Z. Pan +4

In knowledge graph completion (KGC), predicting triples involving emerging entities and/or relations, which are unseen when the KG embeddings are learned, has become a critical cha…

cs.CV2022★ 1 cited

LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection

Zhuo Chen, Yufeng Huang, Jiaoyan Chen +5

Visual question answering (VQA) often requires an understanding of visual concepts and language semantics, which relies on external knowledge. Most existing methods exploit pre-tra…

cs.CV2022★ 3 cited

DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning

Zhuo Chen, Yufeng Huang, Jiaoyan Chen +5

Zero-shot learning (ZSL) aims to predict unseen classes whose samples have never appeared during training. One of the most effective and widely used semantic information for zero-s…

cs.AI2022

Disentangled Ontology Embedding for Zero-shot Learning

Yuxia Geng, Jiaoyan Chen, Wen Zhang +6

Knowledge Graph (KG) and its variant of ontology have been widely used for knowledge representation, and have shown to be quite effective in augmenting Zero-shot Learning (ZSL). Ho…

cs.AI2022★ 1 cited

Contextual Semantic Embeddings for Ontology Subsumption Prediction

Jiaoyan Chen, Yuan He, Yuxia Geng +3

Automating ontology construction and curation is an important but challenging task in knowledge engineering and artificial intelligence. Prediction by machine learning techniques s…