Conjugate Relation Modeling for Few-Shot Knowledge Graph Completion

2025/10/26 by Wang, Zilong, Zeng, Qingtian, Duan, Hua +3
#Computation and Language (cs.CL) #FOS: Computer and information sciences

paper · doi:10.48550/arxiv.2510.22656

Abstract

Few-shot Knowledge Graph Completion (FKGC) infers missing triples from limited support samples, tackling long-tail distribution challenges. Existing methods, however, struggle to capture complex relational patterns and mitigate data sparsity. To address these challenges, we propose a novel FKGC framework for conjugate relation modeling (CR-FKGC). Specifically, it employs a neighborhood aggregation encoder to integrate higher-order neighbor information, a conjugate relation learner combining an implicit conditional diffusion relation module with a stable relation module to capture stable semantics and uncertainty offsets, and a manifold conjugate decoder for efficient evaluation and inference of missing triples in manifold space. Experiments on three benchmarks demonstrate that our method achieves superior performance over state-of-the-art methods.

Citations

• Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion
• Relation-Aware Network with Attention-Based Loss for Few-Shot Knowledge Graph Completion
• DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps
• Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completion
• Score-Based Generative Modeling through Stochastic Differential Equations
• Denoising Diffusion Implicit Models
• Denoising Diffusion Probabilistic Models
• Few-Shot Knowledge Graph Completion
• One-Shot Relational Learning for Knowledge Graphs
• Conditional Neural Processes
• Complex Embeddings for Simple Link Prediction
• Embedding Entities and Relations for Learning and Inference in Knowledge Bases
• Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs

Related

• Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completion
• Learning Relation-Specific Representations for Few-shot Knowledge Graph Completion
• Hierarchical Relational Learning for Few-Shot Knowledge Graph Completion
• KERMIT: Knowledge Graph Completion of Enhanced Relation Modeling with Inverse Transformation
• Tackling Long-Tailed Relations and Uncommon Entities in Knowledge Graph Completion