A survey on temporal knowledge graph completion: Taxonomy, progress, and prospects

J Wang, B Wang, M Qiu, S Pan, B **ong, H Liu… - arxiv preprint arxiv …, 2023 - arxiv.org
Temporal characteristics are prominently evident in a substantial volume of knowledge,
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

Q Liu, S Feng, M Huang, UA Bhatti - Artificial Intelligence Review, 2024 - Springer
The task of predicting entities and relations in Temporal Knowledge Graph (TKG)
extrapolation is crucial and has been studied extensively. Mainstream algorithms, such as …

A survey on temporal knowledge graph embedding: Models and applications

Y Zhang, X Kong, Z Shen, J Li, Q Yi, G Shen… - Knowledge-Based …, 2024 - Elsevier
Abstract Knowledge graph embedding (KGE), as a pivotal technology in artificial
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

Q Li, B Feng, X Tang, H Yu, H Song - Neural Networks, 2024 - Elsevier
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 …

zrLLM: Zero-shot relational learning on temporal knowledge graphs with large language models

Z Ding, H Cai, J Wu, Y Ma, R Liao, B **ong… - arxiv preprint arxiv …, 2023 - arxiv.org
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 …

Improving few-shot inductive learning on temporal knowledge graphs using confidence-augmented reinforcement learning

Z Ding, J Wu, Z Li, Y Ma, V Tresp - Joint European Conference on …, 2023 - Springer
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 …

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 …

Beyond Transduction: A Survey on Inductive, Few Shot, and Zero Shot Link Prediction in Knowledge Graphs

N Hubert, P Monnin, H Paulheim - arxiv preprint arxiv:2312.04997, 2023 - arxiv.org
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 …

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 …

Twin graph attention network with evolution pattern learner for few-shot temporal knowledge graph completion

Y Liang, S Zhao, B Cheng, H Yang - International Conference on …, 2023 - Springer
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 …