Knowledge Graph Completion
7개 벤치마크 · 논문 541편 · 이 태스크의 논문 보기 →
Benchmarks
FB15k-237
DBP-5L (English)
DBP-5L (Greek)
DPB-5L (French)
WN18RR
DBbook2014
MovieLens 1M
Most implemented
Inductive Relation Prediction by Subgraph Reasoning
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey
TuckER: Tensor Factorization for Knowledge Graph Completion
Multi-Relational Embedding for Knowledge Graph Representation and Analysis
Papers
LLM-Based Knowledge Graph Completion Combining Discrete Structural Coding with Similar Entity Information
Knowledge graph completion requires models to use both textual descriptions and relational structure. Existing LLM-based methods either encode KG structure as discrete tokens or refine a restricted set of candidate entit…
Knowledge Graph CompletionViSR-KGC: Visual Subgraph Reasoning with Vision-Language Models for Multimodal Knowledge Graph Completion
Knowledge graph completion (KGC) aims to infer missing entities or relations from incomplete graph structures, and has evolved into multimodal knowledge graph completion (MMKGC), where entities are associated with multip…
Knowledge Graph CompletionRepresentation LearningMultimodal ReasoningKnowledge GraphsDual-Path LLM Reasoning for Multimodal Few-Shot Knowledge Graph Completion
Knowledge graph completion (KGC) aims to infer missing facts in knowledge graphs (KGs), thereby improving their completeness and supporting downstream intelligent applications. However, emerging entities and relations in…
Knowledge Graph CompletionKnowledge GraphsSentence Splitter: Uncovering Latent Factual Structure for Self-Supervised Learning
This paper introduces Sentence Splitter, a self-supervised framework built upon a T5-based encoder--decoder architecture for uncovering the latent factual structure of natural language sentences. The proposed method iden…
Knowledge Graph CompletionSelf-Supervised LearningQuestion AnsweringMGDT: MLLM-Guided Diffusion Transformer with Relation-Adaptive Mixture-of-Experts for Multimodal Knowledge Graph Completion
Multimodal Knowledge Graph Completion (MKGC) requires inferring missing entities from structural, textual, and visual cues. Existing diffusion-based MKGC methods usually denoise directly on raw multimodal features. Such …
Knowledge Graph CompletionConditional Diffusion Guided Knowledge Transfer for Multi-Domain Knowledge Graph Completion
Multi-domain knowledge graph completion (MKGC) aims to improve missing triple prediction in a target KG by transferring knowledge from other support KGs. Existing methods typically enforce consistency constraints on equi…
Knowledge Graph Completion