Search Results for author: Yushan Zhu

Found 8 papers, 6 papers with code

Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey

2 code implementations8 Feb 2024 Zhuo Chen, Yichi Zhang, Yin Fang, Yuxia Geng, Lingbing Guo, Xiang Chen, Qian Li, Wen Zhang, Jiaoyan Chen, Yushan Zhu, Jiaqi Li, Xiaoze Liu, Jeff Z. Pan, Ningyu Zhang, Huajun Chen

In this survey, we carefully review over 300 articles, focusing on KG-aware research in two principal aspects: KG-driven Multi-Modal (KG4MM) learning, where KGs support multi-modal tasks, and Multi-Modal Knowledge Graph (MM4KG), which extends KG studies into the MMKG realm.

Entity Alignment Image Classification +4

Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer

1 code implementation3 Mar 2023 Wen Zhang, Yushan Zhu, Mingyang Chen, Yuxia Geng, Yufeng Huang, Yajing Xu, Wenting Song, Huajun Chen

Through experiments, we justify that the pretrained KGTransformer could be used off the shelf as a general and effective KRF module across KG-related tasks.

Image Classification Knowledge Graphs +3

Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embedding

1 code implementation3 Feb 2023 Mingyang Chen, Wen Zhang, Zhen Yao, Yushan Zhu, Yang Gao, Jeff Z. Pan, Huajun Chen

In our proposed model, Entity-Agnostic Representation Learning (EARL), we only learn the embeddings for a small set of entities and refer to them as reserved entities.

Entity Embeddings Knowledge Graph Embedding +3

Meta-Knowledge Transfer for Inductive Knowledge Graph Embedding

1 code implementation27 Oct 2021 Mingyang Chen, Wen Zhang, Yushan Zhu, Hongting Zhou, Zonggang Yuan, Changliang Xu, Huajun Chen

In this paper, to achieve inductive knowledge graph embedding, we propose a model MorsE, which does not learn embeddings for entities but learns transferable meta-knowledge that can be used to produce entity embeddings.

Entity Embeddings Inductive Relation Prediction +6

Explaining Knowledge Graph Embedding via Latent Rule Learning

no code implementations29 Sep 2021 Wen Zhang, Mingyang Chen, Zezhong Xu, Yushan Zhu, Huajun Chen

KGExplainer is a multi-hop reasoner learning latent rules for link prediction and is encouraged to behave similarly to KGEs during prediction through knowledge distillation.

Knowledge Distillation Knowledge Graph Embedding +3

DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning

no code implementations13 Sep 2020 Yushan Zhu, Wen Zhang, Mingyang Chen, Hui Chen, Xu Cheng, Wei zhang, Huajun Chen

In DualDE, we propose a soft label evaluation mechanism to adaptively assign different soft label and hard label weights to different triples, and a two-stage distillation approach to improve the student's acceptance of the teacher.

Knowledge Distillation Knowledge Graph Embedding +2

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