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 …
VideoINSTA: Zero-shot Long Video Understanding via Informative Spatial-Temporal Reasoning with LLMs
In the video-language domain, recent works in leveraging zero-shot Large Language Model-
based reasoning for video understanding have become competitive challengers to previous …
based reasoning for video understanding have become competitive challengers to previous …
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 …
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 …
TempCaps: a capsule network-based embedding model for temporal knowledge graph completion
Temporal knowledge graphs store the dynamics of entities and relations during a time
period. However, typical temporal knowledge graphs often suffer from incomplete dynamics …
period. However, typical temporal knowledge graphs often suffer from incomplete dynamics …
[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 …
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 …
Chain-of-history reasoning for temporal knowledge graph forecasting
Abstract Temporal Knowledge Graph (TKG) forecasting aims to predict future facts based on
given histories. Most recent graph-based models excel at capturing structural information …
given histories. Most recent graph-based models excel at capturing structural information …
Enhancing temporal knowledge graph forecasting with large language models via chain-of-history reasoning
Temporal Knowledge Graph (TKG) forecasting aims to predict future facts based on given
histories. Most recent graph-based models excel at capturing structural information within …
histories. Most recent graph-based models excel at capturing structural information within …