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cs.CV2024

Multi-level Matching Network for Multimodal Entity Linking

Zhiwei Hu, Víctor Gutiérrez-Basulto, Ru Li +1

Multimodal entity linking (MEL) aims to link ambiguous mentions within multimodal contexts to corresponding entities in a multimodal knowledge base. Most existing approaches to MEL…

cs.LG2024

Contrast All the Time: Learning Time Series Representation from Temporal Consistency

Abdul-Kazeem Shamba, Kerstin Bach, Gavin Taylor

Representation learning for time series using contrastive learning has emerged as a critical technique for improving the performance of downstream tasks. To advance this effective…

cs.AI2024

COTET: Cross-view Optimal Transport for Knowledge Graph Entity Typing

Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2

Knowledge graph entity typing (KGET) aims to infer missing entity type instances in knowledge graphs. Previous research has predominantly centered around leveraging contextual info…

cs.IR2024

Leveraging Intra-modal and Inter-modal Interaction for Multi-Modal Entity Alignment

Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2

Multi-modal entity alignment (MMEA) aims to identify equivalent entity pairs across different multi-modal knowledge graphs (MMKGs). Existing approaches focus on how to better encod…

cs.AI2024

HyperMono: A Monotonicity-aware Approach to Hyper-Relational Knowledge Representation

Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2

In a hyper-relational knowledge graph (HKG), each fact is composed of a main triple associated with attribute-value qualifiers, which express additional factual knowledge. The hype…

cs.CV2024

Knowledge-Aware Neuron Interpretation for Scene Classification

Yong Guan, Freddy Lecue, Jiaoyan Chen +2

Although neural models have achieved remarkable performance, they still encounter doubts due to the intransparency. To this end, model prediction explanation is attracting more and…