https://github.com/KotoHanon/LOCOCO
공식 코드Walk Wisely on Graph: Knowledge Graph Reasoning with Dual Agents via Efficient Guidance-Exploration
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Walk Wisely on Graph: Knowledge Graph Reasoning with Dual Agents via Efficient Guidance-Exploration
Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
An Adversarial Transfer Network for Knowledge Representation Learning
An original model for multi-target learning of logical rules for knowledge graph reasoning
Large Language Models as Interpolated and Extrapolated Event Predictors
EchoEA: Echo Information between Entities and Relations for Entity Alignment
RelWalk A Latent Variable Model Approach to Knowledge Graph Embedding
ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs
Duality-Induced Regularizer for Tensor Factorization Based Knowledge Graph Completion
Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
KEHRL: Learning Knowledge-Enhanced Language Representations with Hierarchical Reinforcement Learning
Multilingual Knowledge Graph Completion from Pretrained Language Models with Knowledge Constraints
Matching Entities Across Different Knowledge Graphs with Graph Embeddings
Feature-based reformulation of entities in triple pattern queries
Zero-Shot Question Generation from Knowledge Graphs for Unseen Predicates and Entity Types
Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings
HGE: Embedding Temporal Knowledge Graphs in a Product Space of Heterogeneous Geometric Subspaces
A Retrieve-and-Read Framework for Knowledge Graph Link Prediction
Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs
Application of Knowledge Graphs to Provide Side Information for Improved Recommendation Accuracy
Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning
Distance-aware Molecule Graph Attention Network for Drug-Target Binding Affinity Prediction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.