1.2k citations · 1.3k across the 12 of their papers we have counts for
12 papers
A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects
Jiapu Wang, Boyue Wang, Meikang Qiu +8
Temporal characteristics are prominently evident in a substantial volume of knowledge, which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia and i…
Towards Few-shot Inductive Link Prediction on Knowledge Graphs: A Relational Anonymous Walk-guided Neural Process Approach
Zicheng Zhao, Linhao Luo, Shirui Pan +2
Few-shot inductive link prediction on knowledge graphs (KGs) aims to predict missing links for unseen entities with few-shot links observed. Previous methods are limited to transdu…
Unifying Large Language Models and Knowledge Graphs: A Roadmap
Shirui Pan, Linhao Luo, Yufei Wang +3
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the field of natural language processing and artificial intelligence, due to their emergent ability…
SocialDial: A Benchmark for Socially-Aware Dialogue Systems
Haolan Zhan, Zhuang Li, Yufei Wang +10
Dialogue systems have been widely applied in many scenarios and are now more powerful and ubiquitous than ever before. With large neural models and massive available data, current…
Normalizing Flow-based Neural Process for Few-Shot Knowledge Graph Completion
Linhao Luo, Yuan-Fang Li, Gholamreza Haffari +1
Knowledge graphs (KGs), as a structured form of knowledge representation, have been widely applied in the real world. Recently, few-shot knowledge graph completion (FKGC), which ai…
Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs
Linhao Luo, Reza Haffari, Shirui Pan
Link prediction on dynamic graphs is an important task in graph mining. Existing approaches based on dynamic graph neural networks (DGNNs) typically require a significant amount of…
GSim: A Graph Neural Network based Relevance Measure for Heterogeneous Graphs
Linhao Luo, Yixiang Fang, Moli Lu +3
Heterogeneous graphs, which contain nodes and edges of multiple types, are prevalent in various domains, including bibliographic networks, social media, and knowledge graphs. As a…
RMGN: A Regional Mask Guided Network for Parser-free Virtual Try-on
Chao Lin, Zhao Li, Sheng Zhou +6
Virtual try-on(VTON) aims at fitting target clothes to reference person images, which is widely adopted in e-commerce.Existing VTON approaches can be narrowly categorized into Pars…
MAMDR: A Model Agnostic Learning Method for Multi-Domain Recommendation
Linhao Luo, Yumeng Li, Buyu Gao +7
Large-scale e-commercial platforms in the real-world usually contain various recommendation scenarios (domains) to meet demands of diverse customer groups. Multi-Domain Recommendat…
Detecting Communities from Heterogeneous Graphs: A Context Path-based Graph Neural Network Model
Linhao Luo, Yixiang Fang, Xin Cao +2
Community detection, aiming to group the graph nodes into clusters with dense inner-connection, is a fundamental graph mining task. Recently, it has been studied on the heterogeneo…
RRCN: A Reinforced Random Convolutional Network based Reciprocal Recommendation Approach for Online Dating
Linhao Luo, Liqi Yang, Ju Xin +6
Recently, the reciprocal recommendation, especially for online dating applications, has attracted more and more research attention. Different from conventional recommendation probl…
Structure Matters: Towards Generating Transferable Adversarial Images
Dan Peng, Zizhan Zheng, Linhao Luo +1
Recent works on adversarial examples for image classification focus on directly modifying pixels with minor perturbations. The small perturbation requirement is imposed to ensure t…