Papers with Code 아카이브
Triple Classification
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
- 1
- 평가표
- 1
- 보존된 평가 기록
- 1
Triple classification aims to judge whether a given triple (h, r, t) is correct or not with respect to the knowledge graph.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
From Latent to Lucid: Transforming Knowledge Graph Embeddings into Interpretable Structures with KGEPrisma
Towards Knowledge-Infused Automated Disease Diagnosis Assistant
Untargeted Adversarial Attack on Knowledge Graph Embeddings
RAG-based Explainable Prediction of Road Users Behaviors for Automated Driving using Knowledge Graphs and Large Language Models
Sharing Parameter by Conjugation for Knowledge Graph Embeddings in Complex Space
Progressive Knowledge Graph Completion
KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptation
Counterfactual Reasoning with Knowledge Graph Embeddings
BloomGML: Graph Machine Learning through the Lens of Bilevel Optimization
Federated Neural Graph Databases
Improving Molecule Generation and Drug Discovery with a Knowledge-enhanced Generative Model
Empowering machine learning models with contextual knowledge for enhancing the detection of eating disorders in social media posts
Embedding Knowledge Graphs in Degenerate Clifford Algebras
Capturing Knowledge Graphs and Rules with Octagon Embeddings
Pre-training and Diagnosing Knowledge Base Completion Models
Embedding Ontologies via Incorporating Extensional and Intensional Knowledge
Towards Efficient Methods in Medical Question Answering using Knowledge Graph Embeddings
Block-Diagonal Orthogonal Relation and Matrix Entity for Knowledge Graph Embedding
BEV-TSR: Text-Scene Retrieval in BEV Space for Autonomous Driving
RDF-star2Vec: RDF-star Graph Embeddings for Data Mining
Vehicle Lane Change Prediction based on Knowledge Graph Embeddings and Bayesian Inference
Linked Papers With Code: The Latest in Machine Learning as an RDF Knowledge Graph
EXTRACT: Explainable Transparent Control of Bias in Embeddings
Faithful Path Language Modeling for Explainable Recommendation over Knowledge Graph
A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of Things
Universal Knowledge Graph Embeddings
Accurate prediction of international trade flows: Leveraging knowledge graphs and their embeddings
KGEx: Explaining Knowledge Graph Embeddings via Subgraph Sampling and Knowledge Distillation
Leveraging Pre-trained Language Models for Time Interval Prediction in Text-Enhanced Temporal Knowledge Graphs
Clinical Trial Recommendations Using Semantics-Based Inductive Inference and Knowledge Graph Embeddings
Universal Preprocessing Operators for Embedding Knowledge Graphs with Literals
Knowledge Graph Embeddings for Multi-Lingual Structured Representations of Radiology Reports
Large language models converge toward human-like concept organization
Exploring Large Language Models for Knowledge Graph Completion
Leveraging Knowledge and Reinforcement Learning for Enhanced Reliability of Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.