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Knowledge Graphs

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하위 태스크: 5
평가표: 4
보존된 평가 기록: 19

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/xiangwang1223/knowledge_graph_attention_network

공식 코드

KGAT: Knowledge Graph Attention Network for Recommendation

https://github.com/xiaohui-victor-li/FinDKG

공식 코드

FinDKG: Dynamic Knowledge Graphs with Large Language Models for Detecting Global Trends in Financial Markets

https://github.com/xiaoiker/Awesome-Hyperbolic-NeuralNetworks

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Hyperbolic Deep Neural Networks: A Survey

https://github.com/xiaojuantang/rule

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RulE: Knowledge Graph Reasoning with Rule Embedding

https://github.com/xiaomingaaa/biokdn

공식 코드

Learning to Denoise Biomedical Knowledge Graph for Robust Molecular Interaction Prediction

https://github.com/xiaomingaaa/sdn

공식 코드

S$^2$DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph Completion

https://github.com/xiaoqian19940510/moalign

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Multi-Modal Knowledge Graph Transformer Framework for Multi-Modal Entity Alignment

https://github.com/xiefeng69/gaea

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Improving Knowledge Graph Entity Alignment with Graph Augmentation

https://github.com/xincanfeng/dimension

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Sharing Parameter by Conjugation for Knowledge Graph Embeddings in Complex Space

https://github.com/xincanfeng/ms_kge

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Model-based Subsampling for Knowledge Graph Completion

https://github.com/xincanfeng/ss_kge

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Unified Interpretation of Smoothing Methods for Negative Sampling Loss Functions in Knowledge Graph Embedding

https://github.com/xingdi-eric-yuan/GATA-public

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Learning Dynamic Belief Graphs to Generalize on Text-Based Games

https://github.com/xingdi-eric-yuan/imrc_graph_public

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Interactive Machine Comprehension with Dynamic Knowledge Graphs

https://github.com/xinyulin-fz/lenie

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Node Importance Estimation Leveraging LLMs for Semantic Augmentation in Knowledge Graphs

https://github.com/xiongbo010/neste

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NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning

https://github.com/xiongbo010/shrinke

공식 코드

Shrinking Embeddings for Hyper-Relational Knowledge Graphs

https://github.com/xiongsiheng/tilp

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TILP: Differentiable Learning of Temporal Logical Rules on Knowledge Graphs

https://github.com/xjtuwgt/gnn-magna

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Multi-hop Attention Graph Neural Network

https://github.com/xuan-zw/lkpnr

공식 코드

LKPNR: LLM and KG for Personalized News Recommendation Framework

https://github.com/xwhan/DeepPath

공식 코드

DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning

https://github.com/xwhan/One-shot-Relational-Learning

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One-Shot Relational Learning for Knowledge Graphs

https://github.com/xxrep/golde

공식 코드

Generalizing Knowledge Graph Embedding with Universal Orthogonal Parameterization

https://github.com/xz-liu/grapheval

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Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs

https://github.com/yandex-research/sparqling-queries

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SPARQLing Database Queries from Intermediate Question Decompositions

https://github.com/yangrui525/kg-rank

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KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques

https://github.com/yanmenxue/rah-kbqa

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Relation-Aware Question Answering for Heterogeneous Knowledge Graphs

https://github.com/yanxuzhu/kg-fpq

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KG-FPQ: Evaluating Factuality Hallucination in LLMs with Knowledge Graph-based False Premise Questions

https://github.com/yao8839836/kg-bert

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KG-BERT: BERT for Knowledge Graph Completion

https://github.com/yao8839836/kg-llm

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Exploring Large Language Models for Knowledge Graph Completion

https://github.com/yaooxu/gog

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Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question Answering

https://github.com/yaooxu/q2t

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Query2Triple: Unified Query Encoding for Answering Diverse Complex Queries over Knowledge Graphs

https://github.com/ycm094/mg-fte-main

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Mutually Guided Few-shot Learning for Relational Triple Extraction

https://github.com/yeeeqichen/fits

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FiTs: Fine-grained Two-stage Training for Knowledge-aware Question Answering

https://github.com/yide-qiu/unikg

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UniKG: A Benchmark and Universal Embedding for Large-Scale Knowledge Graphs

https://github.com/yifan-h/multilingual_space

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Adapters for Enhanced Modeling of Multilingual Knowledge and Text

https://github.com/yihong-chen/refactorgnn

공식 코드

ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspective

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