Unifying large language models and knowledge graphs: A roadmap
Large language models (LLMs), such as ChatGPT and GPT4, are making new waves in the
field of natural language processing and artificial intelligence, due to their emergent ability …
field of natural language processing and artificial intelligence, due to their emergent ability …
Llms for knowledge graph construction and reasoning: Recent capabilities and future opportunities
This paper presents an exhaustive quantitative and qualitative evaluation of Large
Language Models (LLMs) for Knowledge Graph (KG) construction and reasoning. We …
Language Models (LLMs) for Knowledge Graph (KG) construction and reasoning. We …
[PDF][PDF] Knowledge Graph Embedding: An Overview
Many mathematical models have been leveraged to design embeddings for representing
Knowledge Graph (KG) entities and relations for link prediction and many downstream tasks …
Knowledge Graph (KG) entities and relations for link prediction and many downstream tasks …
A review of graph neural networks and pretrained language models for knowledge graph reasoning
J Ma, B Liu, K Li, C Li, F Zhang, X Luo, Y Qiao - Neurocomputing, 2024 - Elsevier
Abstract Knowledge Graph (KG) stores human knowledge facts in an intuitive graphical
structure but faces challenges such as incomplete construction or inability to handle new …
structure but faces challenges such as incomplete construction or inability to handle new …
Kicgpt: Large language model with knowledge in context for knowledge graph completion
Knowledge Graph Completion (KGC) is crucial for addressing knowledge graph
incompleteness and supporting downstream applications. Many models have been …
incompleteness and supporting downstream applications. Many models have been …
Editing language model-based knowledge graph embeddings
Recently decades have witnessed the empirical success of framing Knowledge Graph (KG)
embeddings via language models. However, language model-based KG embeddings are …
embeddings via language models. However, language model-based KG embeddings are …
[PDF][PDF] Pre-dygae: Pre-training enhanced dynamic graph autoencoder for occupational skill demand forecasting
Occupational skill demand (OSD) forecasting seeks to predict dynamic skill demand specific
to occupations, beneficial for employees and employers to grasp occupational nature and …
to occupations, beneficial for employees and employers to grasp occupational nature and …
Learning joint structural and temporal contextualized knowledge embeddings for temporal knowledge graph completion
Temporal knowledge graph completion that predicts missing links for incomplete temporal
knowledge graphs (TKG) is gaining increasing attention. Most existing works have achieved …
knowledge graphs (TKG) is gaining increasing attention. Most existing works have achieved …
Simple Yet Effective: Structure Guided Pre-trained Transformer for Multi-modal Knowledge Graph Reasoning
Various information in different modalities in an intuitive way in multi-modal knowledge
graphs (MKGs), which are utilized in different downstream tasks, like recommendation …
graphs (MKGs), which are utilized in different downstream tasks, like recommendation …
A knowledge graph completion model based on triple level interaction and contrastive learning
J Hu, H Yang, F Teng, S Du, T Li - Pattern Recognition, 2024 - Elsevier
Abstract Knowledge graphs provide credible and structured knowledge for downstream
tasks such as information retrieval. Nevertheless, the ubiquitous incompleteness of …
tasks such as information retrieval. Nevertheless, the ubiquitous incompleteness of …