6 citations · 10 across the 9 of their papers we have counts for
11 papers
Plan Then Retrieve: Reinforcement Learning-Guided Complex Reasoning over Knowledge Graphs
Yanlin Song, Ben Liu, Víctor Gutiérrez-Basulto +5
Knowledge Graph Question Answering aims to answer natural language questions by reasoning over structured knowledge graphs. While large language models have advanced KGQA through t…
Multi-level Mixture of Experts for Multimodal Entity Linking
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
Multimodal Entity Linking (MEL) aims to link ambiguous mentions within multimodal contexts to associated entities in a multimodal knowledge base. Existing approaches to MEL introdu…
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…
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…
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…
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…
Multi-view Contrastive Learning for Entity Typing over Knowledge Graphs
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
Knowledge graph entity typing (KGET) aims at inferring plausible types of entities in knowledge graphs. Existing approaches to KGET focus on how to better encode the knowledge prov…
HyperFormer: Enhancing Entity and Relation Interaction for Hyper-Relational Knowledge Graph Completion
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
Hyper-relational knowledge graphs (HKGs) extend standard knowledge graphs by associating attribute-value qualifiers to triples, which effectively represent additional fine-grained…
Transformer-based Entity Typing in Knowledge Graphs
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +2
We investigate the knowledge graph entity typing task which aims at inferring plausible entity types. In this paper, we propose a novel Transformer-based Entity Typing (TET) approa…
Type-aware Embeddings for Multi-Hop Reasoning over Knowledge Graphs
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang +3
Multi-hop reasoning over real-life knowledge graphs (KGs) is a highly challenging problem as traditional subgraph matching methods are not capable to deal with noise and missing in…
Youling: an AI-Assisted Lyrics Creation System
Rongsheng Zhang, Xiaoxi Mao, Le Li +6
Recently, a variety of neural models have been proposed for lyrics generation. However, most previous work completes the generation process in a single pass with little human inter…