2 citations · 3 across the 2 of their papers we have counts for
12 papers
A Language Model based Framework for New Concept Placement in Ontologies
Hang Dong, Jiaoyan Chen, Yuan He +2
We investigate the task of inserting new concepts extracted from texts into an ontology using language models. We explore an approach with three steps: edge search which is to find…
Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey
Zhuo Chen, Yichi Zhang, Yin Fang +12
Knowledge Graphs (KGs) play a pivotal role in advancing various AI applications, with the semantic web community's exploration into multi-modal dimensions unlocking new avenues for…
Exploring the Impact of Table-to-Text Methods on Augmenting LLM-based Question Answering with Domain Hybrid Data
Dehai Min, Nan Hu, Rihui Jin +8
Augmenting Large Language Models (LLMs) for Question Answering (QA) with domain specific data has attracted wide attention. However, domain data often exists in a hybrid format, in…
Knowledge-Aware Neuron Interpretation for Scene Classification
Yong Guan, Freddy Lecue, Jiaoyan Chen +2
Although neural models have achieved remarkable performance, they still encounter doubts due to the intransparency. To this end, model prediction explanation is attracting more and…
Exploring Large Language Models for Ontology Alignment
Yuan He, Jiaoyan Chen, Hang Dong +1
This work investigates the applicability of recent generative Large Language Models (LLMs), such as the GPT series and Flan-T5, to ontology alignment for identifying concept equiva…
Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment
Zhuo Chen, Lingbing Guo, Yin Fang +6
As a crucial extension of entity alignment (EA), multi-modal entity alignment (MMEA) aims to identify identical entities across disparate knowledge graphs (KGs) by exploiting assoc…