LLM+KG@VLDB'24 Workshop Summary
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Abstract (arXiv)
The unification of large language models (LLMs) and knowledge graphs (KGs) has emerged as a hot topic. At the LLM+KG'24 workshop, held in conjunction with VLDB 2024 in Guangzhou, China, one of the key themes explored was important data management challenges and opportunities due to the effective interaction between LLMs and KGs. This report outlines the major directions and approaches presented by various speakers during the LLM+KG'24 workshop.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 32 of its 57 references that are in the map. First posted on arXiv 2 Oct 2024.
Builds on
32 of 57 references.
References · 32
- 2019Language Models as Knowledge Bases?cited by 1,922
- 2024From Local to Global: A Graph RAG Approach to Query-Focused Summarizationcited by 1,411
- 2019Generalization through Memorization: Nearest Neighbor Language Modelscited by 788
- 2023Unifying Large Language Models and Knowledge Graphs: A Roadmapcited by 663
- 2023Editing Large Language Models: Problems, Methods, and Opportunitiescited by 367
- 2023Can We Edit Factual Knowledge by In-Context Learning?cited by 284
- 2024HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Modelscited by 273
- 2020A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphscited by 119
- 2024Retrieval-Augmented Generation with Knowledge Graphs for Customer Service Question Answeringcited by 95
- 2020JAKET: Joint Pre-training of Knowledge Graph and Language Understandingcited by 73
- 2023Can ChatGPT Replace Traditional KBQA Models? An In-depth Analysis of the Question Answering Performance of the GPT LLM Familycited by 71
- 2024KG-RAG: Bridging the Gap Between Knowledge and Creativitycited by 55
20 more
- 2023Making Large Language Models Perform Better in Knowledge Graph Completioncited by 48
- 2024KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completioncited by 36
- 2023OLaLa: Ontology Matching with Large Language Modelscited by 35
- 2024A Declarative System for Optimizing AI Workloadscited by 35
- 2023InstructProtein: Aligning Human and Protein Language via Knowledge Instructioncited by 27
- 2024SPADE: Synthesizing Data Quality Assertions for Large Language Model Pipelinescited by 19
- 2024InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integrationcited by 19
- 2024Unlocking the Power of Large Language Models for Entity Alignmentcited by 15
- 2024Research Trends for the Interplay between Large Language Models and Knowledge Graphscited by 14
- 2023Revisiting Prompt Engineering via Declarative Crowdsourcingcited by 12
- 2024OneEdit: A Neural-Symbolic Collaboratively Knowledge Editing Systemcited by 12
- 2024KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptationcited by 10
- 2024Evidence-Focused Fact Summarization for Knowledge-Augmented Zero-Shot Question Answeringcited by 9
- 2023Deep Active Alignment of Knowledge Graph Entities and Schematacited by 6
- 2023Serial Contrastive Knowledge Distillation for Continual Few-shot Relation Extractioncited by 6
- 2023Continual Event Extraction with Semantic Confusion Rectificationcited by 5
- 2023Generating Explanations to Understand and Repair Embedding-based Entity Alignmentcited by 5
- 2023What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddingscited by 4
- 2024Can Large Language Models Understand DL-Lite Ontologies? An Empirical Studycited by 4
- 2023Benchmarking and Analyzing In-context Learning, Fine-tuning and Supervised Learning for Biomedical Knowledge Curation: a focused study on chemical entities of biological interestcited by 2
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Citing papers per year: 2025: 2; 2026: 1.
3 papers.