5 citations · 14 across the 10 of their papers we have counts for
10 papers
Structure-CLIP: Towards Scene Graph Knowledge to Enhance Multi-modal Structured Representations
Yufeng Huang, Jiji Tang, Zhuo Chen +8
Large-scale vision-language pre-training has achieved significant performance in multi-modal understanding and generation tasks. However, existing methods often perform poorly on i…
Structure Pretraining and Prompt Tuning for Knowledge Graph Transfer
Wen Zhang, Yushan Zhu, Mingyang Chen +5
Knowledge graphs (KG) are essential background knowledge providers in many tasks. When designing models for KG-related tasks, one of the key tasks is to devise the Knowledge Repres…
Analogical Inference Enhanced Knowledge Graph Embedding
Zhen Yao, Wen Zhang, Mingyang Chen +3
Knowledge graph embedding (KGE), which maps entities and relations in a knowledge graph into continuous vector spaces, has achieved great success in predicting missing links in kno…
MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid
Zhuo Chen, Jiaoyan Chen, Wen Zhang +8
Multi-modal entity alignment (MMEA) aims to discover identical entities across different knowledge graphs (KGs) whose entities are associated with relevant images. However, current…
Tele-Knowledge Pre-training for Fault Analysis
Zhuo Chen, Wen Zhang, Yufeng Huang +14
In this work, we share our experience on tele-knowledge pre-training for fault analysis, a crucial task in telecommunication applications that requires a wide range of knowledge no…
Target-oriented Sentiment Classification with Sequential Cross-modal Semantic Graph
Yufeng Huang, Zhuo Chen, Jiaoyan Chen +3
Multi-modal aspect-based sentiment classification (MABSC) is task of classifying the sentiment of a target entity mentioned in a sentence and an image. However, previous methods fa…
LaKo: Knowledge-driven Visual Question Answering via Late Knowledge-to-Text Injection
Zhuo Chen, Yufeng Huang, Jiaoyan Chen +5
Visual question answering (VQA) often requires an understanding of visual concepts and language semantics, which relies on external knowledge. Most existing methods exploit pre-tra…
DUET: Cross-modal Semantic Grounding for Contrastive Zero-shot Learning
Zhuo Chen, Yufeng Huang, Jiaoyan Chen +5
Zero-shot learning (ZSL) aims to predict unseen classes whose samples have never appeared during training. One of the most effective and widely used semantic information for zero-s…
Disentangled Ontology Embedding for Zero-shot Learning
Yuxia Geng, Jiaoyan Chen, Wen Zhang +6
Knowledge Graph (KG) and its variant of ontology have been widely used for knowledge representation, and have shown to be quite effective in augmenting Zero-shot Learning (ZSL). Ho…
NeuralKG: An Open Source Library for Diverse Representation Learning of Knowledge Graphs
Wen Zhang, Xiangnan Chen, Zhen Yao +10
NeuralKG is an open-source Python-based library for diverse representation learning of knowledge graphs. It implements three different series of Knowledge Graph Embedding (KGE) met…