2 citations · 3 across the 12 of their papers we have counts for
11 papers
TimeRoute: Time-Aware Modality Routing and Diffusion for Multi-Modal Recommendation
Pengyu Zhang, Yangqin Jiang, Klim Zaporojets +2
Multi-modal recommenders fuse user-item interaction signals with item modalities such as text, images, and audio, but the usefulness of each drifts over time and at different rates…
Select, Don't Train: The Benefits of Modular Entity Disambiguation with LLM-Based Selection
Fina Polat, Daniel Daza, Pengyu Zhang +2
Entity Disambiguation (ED) is a key task for constructing and using knowledge graphs. State-of-the-art neural approaches commonly model ED as a single task, although it consists of…
Time Imprint: Learning Time-Aware Representations in Multi-Modal Knowledge Graphs
Pengyu Zhang, Klim Zaporojets, Congfeng Cao +2
Multi-Modal Knowledge Graphs (MMKGs) enrich entities with multiple modalities such as text and images, yet entities with highly similar multi-modal features remain difficult to dis…
Are a Thousand Words Better Than a Single Picture? Beyond Images -- A Framework for Multi-Modal Knowledge Graph Dataset Enrichment
Pengyu Zhang, Klim Zaporojets, Jie Liu +2
Multi-Modal Knowledge Graphs (MMKGs) benefit from visual information, yet large-scale image collection is hard to curate and often excludes ambiguous but relevant visuals (e.g., lo…
EMERGE: A Benchmark for Updating Knowledge Graphs with Emerging Textual Knowledge
Klim Zaporojets, Daniel Daza, Edoardo Barba +3
Knowledge Graphs (KGs) are structured knowledge repositories containing entities and relations between them. In this paper, we study the problem of automatically updating KGs over…
A Survey of Large Language Models for Data Challenges in Graphs
Mengran Li, Pengyu Zhang, Wenbin Xing +11
Graphs are a widely used paradigm for representing non-Euclidean data, with applications ranging from social network analysis to biomolecular prediction. While graph learning has a…