https://github.com/INK-USC/DArtNet
공식 코드Temporal Attribute Prediction via Joint Modeling of Multi-Relational Structure Evolution
Papers with Code 아카이브
Knowledge Graphs
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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- 평가표
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A knowledge graph is a structured representation of information that organizes data into nodes (entities) and edges (relationships) to show how different pieces of knowledge are interconnected. It enables enhanced data integration, search, and inference by modeling the relationships between concepts and entities in a graph format.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/INK-USC/HGN
공식 코드Learning Contextualized Knowledge Structures for Commonsense Reasoning
https://github.com/INK-USC/KagNet
공식 코드KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning
https://github.com/INK-USC/MHGRN
공식 코드Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering
https://github.com/INK-USC/RE-Net
공식 코드Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs
https://github.com/INK-USC/SalKG
공식 코드SalKG: Learning From Knowledge Graph Explanations for Commonsense Reasoning
https://github.com/INK-USC/deceive-KG-models
공식 코드Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation
https://github.com/Ipazia-AI/latent-explorer
공식 코드Unveiling LLMs: The Evolution of Latent Representations in a Dynamic Knowledge Graph
https://github.com/JD-AI-Research-Silicon-Valley/SACN
공식 코드End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion
https://github.com/JeanKaddour/WASAM
공식 코드https://github.com/Jeff20100601/GHNN_clean
공식 코드Graph Hawkes Neural Network for Forecasting on Temporal Knowledge Graphs
https://github.com/Jeffrey-Sardina/TWIG-I
공식 코드https://github.com/Jeffrey-Sardina/TWIG-TWM-dev
공식 코드https://github.com/JerichoWorld/JerichoWorld
공식 코드https://github.com/JiapengWu/TeMP
공식 코드TeMP: Temporal Message Passing for Temporal Knowledge Graph Completion
https://github.com/JingruG/GATHER
공식 코드Open-Set Knowledge-Based Visual Question Answering with Inference Paths
https://github.com/Juanhui28/Are_MPNNs_helpful
공식 코드Are Message Passing Neural Networks Really Helpful for Knowledge Graph Completion?
https://github.com/JunhengH/joie-kdd19
공식 코드https://github.com/KGQA/KGQA-datasets-generalization
공식 코드https://github.com/KRR-Oxford/OWL2Vec-Star
공식 코드https://github.com/KnowledgeCaptureAndDiscovery/OBA
공식 코드OBA: An Ontology-Based Framework for Creating REST APIs for Knowledge Graphs
https://github.com/KokiKishimoto/cp_decomposition
공식 코드https://github.com/KokiKishimoto/cp_decomposition_alpha
공식 코드https://github.com/KotoHanon/LOCOCO
공식 코드Walk Wisely on Graph: Knowledge Graph Reasoning with Dual Agents via Efficient Guidance-Exploration
https://github.com/LHY-24/KG-Compilation
공식 코드https://github.com/Lancelot39/KGSF
공식 코드Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
https://github.com/LemonNoel/ATransN
공식 코드An Adversarial Transfer Network for Knowledge Representation Learning
https://github.com/LiGaoJi/MPLR
공식 코드An original model for multi-target learning of logical rules for knowledge graph reasoning
https://github.com/Libo1023/LEAP
공식 코드Large Language Models as Interpolated and Extrapolated Event Predictors
https://github.com/LinXueyuanStdio/EchoEA
공식 코드EchoEA: Echo Information between Entities and Relations for Entity Alignment
https://github.com/LiyingCheng95/EntityDescriptionGeneration
공식 코드ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
https://github.com/MI-911/warm-start-framework
공식 코드MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
https://github.com/MIRALab-USTC/KG-TACT
공식 코드Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs
https://github.com/MIRALab-USTC/KGE-HAKE
공식 코드Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
https://github.com/MMMU-Benchmark/MMMU
공식 코드MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
https://github.com/MaestroGraph/motive-rdf
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.