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A survey on temporal knowledge graph completion: Taxonomy, progress, and prospects
Temporal characteristics are prominently evident in a substantial volume of knowledge,
which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia …
which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia …
Chronobridge: a novel framework for enhanced temporal and relational reasoning in temporal knowledge graphs
The task of predicting entities and relations in Temporal Knowledge Graph (TKG)
extrapolation is crucial and has been studied extensively. Mainstream algorithms, such as …
extrapolation is crucial and has been studied extensively. Mainstream algorithms, such as …
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 …
Mulan: Multi-level attention-enhanced matching network for few-shot knowledge graph completion
Recent years have witnessed increasing interest in the few-shot knowledge graph
completion due to its potential to augment the coverage of few-shot relations in knowledge …
completion due to its potential to augment the coverage of few-shot relations in knowledge …
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 …
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 …
Few-shot multi-hop reasoning via reinforcement learning and path search strategy over temporal knowledge graphs
L Bai, H Zhang, X An, L Zhu - Information Processing & Management, 2025 - Elsevier
Multi-hop reasoning on knowledge graphs is an important way to complete the knowledge
graph. However, existing multi-hop reasoning methods often perform poorly in few-shot …
graph. However, existing multi-hop reasoning methods often perform poorly in few-shot …
Beyond Transduction: A Survey on Inductive, Few Shot, and Zero Shot Link Prediction in Knowledge Graphs
Knowledge graphs (KGs) comprise entities interconnected by relations of different semantic
meanings. KGs are being used in a wide range of applications. However, they inherently …
meanings. KGs are being used in a wide range of applications. However, they inherently …
Few-Shot Knowledge Graph Completion With Star and Ring Topology Information Aggregation
J Zhao, X Zhang, Y Li, S Sun - IEEE Transactions on …, 2025 - ieeexplore.ieee.org
Few-shot knowledge graph completion (FKGC) addresses the long-tail problem of relations
by leveraging a few observed support entity pairs to infer unknown facts for tail-located …
by leveraging a few observed support entity pairs to infer unknown facts for tail-located …
Twin graph attention network with evolution pattern learner for few-shot temporal knowledge graph completion
Recent years have witnessed a growing number of studies on few-shot knowledge graph
completion (FSKGC), which aims to infer new facts for relations given its few-shot observed …
completion (FSKGC), which aims to infer new facts for relations given its few-shot observed …