A survey of knowledge graph reasoning on graph types: Static, dynamic, and multi-modal
Knowledge graph reasoning (KGR), aiming to deduce new facts from existing facts based on
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
mined logic rules underlying knowledge graphs (KGs), has become a fast-growing research …
A survey on temporal knowledge graph embedding: Models and applications
Abstract Knowledge graph embedding (KGE), as a pivotal technology in artificial
intelligence, plays a significant role in enhancing the logical reasoning and management …
intelligence, plays a significant role in enhancing the logical reasoning and management …
Generalizing to unseen elements: A survey on knowledge extrapolation for knowledge graphs
Knowledge graphs (KGs) have become valuable knowledge resources in various
applications, and knowledge graph embedding (KGE) methods have garnered increasing …
applications, and knowledge graph embedding (KGE) methods have garnered increasing …
zrLLM: Zero-Shot Relational Learning on Temporal Knowledge Graphs with Large Language Models
Modeling evolving knowledge over temporal knowledge graphs (TKGs) has become a
heated topic. Various methods have been proposed to forecast links on TKGs. Most of them …
heated topic. Various methods have been proposed to forecast links on TKGs. Most of them …
[PDF][PDF] Gentkg: Generative forecasting on temporal knowledge graph
GenTKG: Generative Forecasting on Temporal Knowledge Graph Page 1 GenTKG: Generative
Forecasting on Temporal Knowledge Graph Ruotong Liao, Xu Jia, Yunpu Ma, Volker Tresp …
Forecasting on Temporal Knowledge Graph Ruotong Liao, Xu Jia, Yunpu Ma, Volker Tresp …
Zero-shot relational learning on temporal knowledge graphs with large language models
In recent years, modeling evolving knowledge over temporal knowledge graphs (TKGs) has
become a heated topic. Various methods have been proposed to forecast links on TKGs …
become a heated topic. Various methods have been proposed to forecast links on TKGs …
Improving few-shot inductive learning on temporal knowledge graphs using confidence-augmented reinforcement learning
Temporal knowledge graph completion (TKGC) aims to predict the missing links among the
entities in a temporal knowledge graph (TKG). Most previous TKGC methods only consider …
entities in a temporal knowledge graph (TKG). Most previous TKGC methods only consider …
GenTKG: Generative Forecasting on Temporal Knowledge Graph with Large Language Models
The rapid advancements in large language models (LLMs) have ignited interest in the
temporal knowledge graph (tKG) domain, where conventional embedding-based and rule …
temporal knowledge graph (tKG) domain, where conventional embedding-based and rule …
A simple but powerful graph encoder for temporal knowledge graph completion
Abstract Knowledge graphs contain rich knowledge about various entities and the relational
information among them, while temporal knowledge graphs (TKGs) describe and model the …
information among them, while temporal knowledge graphs (TKGs) describe and model the …
Learning Meta-Representations of One-shot Relations for Temporal Knowledge Graph Link Prediction
Few-shot relational learning for static knowledge graphs (KGs) has drawn greater interest in
recent years, while few-shot learning for temporal knowledge graphs (TKGs) has hardly …
recent years, while few-shot learning for temporal knowledge graphs (TKGs) has hardly …