Workshop on Deep Learning and Large Language Models for Knowledge Graphs (DL4KG)

被引：0

作者：

Alam, Mehwish ^{[1
]}

Buscaldi, Davide ^{[2
]}

Cochez, Michael ^{[3
]}

Gesese, Genet Asefa ^{[4
]}

Osborne, Francesco ^{[5
]}

Recupero, Diego Reforgiato ^{[6
]}

机构：

[1] Telecom Paris, Inst Polytech Paris, Paris, France

[2] Lab Informat Paris Nord, Paris, France

[3] Vrije Univ Amsterdam, Elsevier Discovery Lab, Comp Sci, Amsterdam, Netherlands

[4] FIZ Karlsruhe, Leibniz Inst Informat Infrastruct, Karlsruhe, Germany

[5] Open Univ, Milton Keynes, Bucks, England

[6] Univ Cagliari, Cagliari, Italy

来源：

PROCEEDINGS OF THE 30TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, KDD 2024 | 2024年

关键词：

Artificial Intelligence; Deep Learning; Large Language Models; Knowledge Graphs;

D O I：

10.1145/3637528.3671491

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The use of Knowledge Graphs (KGs) which constitute large networks of real-world entities and their interrelationships, has grown rapidly. A substantial body of research has emerged, exploring the integration of deep learning (DL) and large language models (LLMs) with KGs. This workshop aims to bring together leading researchers in the field to discuss and foster collaborations on the intersection of KG and DL/LLMs.

引用

页码：6704 / 6705

页数：2