https://github.com/tongzhou21/CogMG
공식 코드CogMG: Collaborative Augmentation Between Large Language Model and Knowledge Graph
Papers with Code 아카이브
Knowledge Graphs
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
- 하위 태스크
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- 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/tqfang/complex-commonsense-reasoning
공식 코드Complex Reasoning over Logical Queries on Commonsense Knowledge Graphs
https://github.com/tranhungnghiep/AnalyzeKGE
공식 코드Analyzing Knowledge Graph Embedding Methods from a Multi-Embedding Interaction Perspective
https://github.com/tranhungnghiep/KG20C
공식 코드Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding Space
https://github.com/tranhungnghiep/MEI-KGE
공식 코드Multi-Partition Embedding Interaction with Block Term Format for Knowledge Graph Completion
https://github.com/tranhungnghiep/meim-kge
공식 코드https://github.com/tree-jhk/reckg
공식 코드https://github.com/truthai-lab/soradetector
공식 코드Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Models
https://github.com/tsafavi/cascader
공식 코드CascadER: Cross-Modal Cascading for Knowledge Graph Link Prediction
https://github.com/tsafavi/codex
공식 코드https://github.com/ttrouill/complex
공식 코드https://github.com/ttrouill/induction_experiments
공식 코드On Inductive Abilities of Latent Factor Models for Relational Learning
https://github.com/tuftsvalt/kgsinpractice
공식 코드https://github.com/txb-nju/exea
공식 코드Generating Explanations to Understand and Repair Embedding-based Entity Alignment
https://github.com/txsun1997/CoLAKE
공식 코드https://github.com/uclnlp/cqd
공식 코드https://github.com/ukp-square/square-core
공식 코드UKP-SQuARE v2: Explainability and Adversarial Attacks for Trustworthy QA
https://github.com/uma-pi1/grash
공식 코드Start Small, Think Big: On Hyperparameter Optimization for Large-Scale Knowledge Graph Embeddings
https://github.com/uma-pi1/kgt5-context
공식 코드Friendly Neighbors: Contextualized Sequence-to-Sequence Link Prediction
https://github.com/uma-pi1/wikidata5m-si
공식 코드A Benchmark for Semi-Inductive Link Prediction in Knowledge Graphs
https://github.com/uq-neusoft-health-data-science/activeea
공식 코드https://github.com/uqbingliu/emea
공식 코드https://github.com/uqbingliu/stea
공식 코드https://github.com/urchade/enrico
공식 코드https://github.com/usail-hkust/urbankgent
공식 코드UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction
https://github.com/usail-hkust/uukg
공식 코드UUKG: Unified Urban Knowledge Graph Dataset for Urban Spatiotemporal Prediction
https://github.com/usc-isi-i2/cskg
공식 코드https://github.com/usc-isi-i2/kgtk
공식 코드KGTK: A Toolkit for Large Knowledge Graph Manipulation and Analysis
https://github.com/usc-isi-i2/kgtk-similarity
공식 코드User-friendly Comparison of Similarity Algorithms on Wikidata
https://github.com/uva-dsa/dkec
공식 코드DKEC: Domain Knowledge Enhanced Multi-Label Classification for Diagnosis Prediction
https://github.com/valence-labs/TxPert
공식 코드https://github.com/vasilikikou/memegraphs
공식 코드https://github.com/vendi12/semantic_coherence
공식 코드https://github.com/vid-koci/kbctransferlearning
공식 코드Pre-training and Diagnosing Knowledge Base Completion Models
https://github.com/vijaydwivedi75/gnn-lspe
공식 코드Graph Neural Networks with Learnable Structural and Positional Representations
https://github.com/vinhsuhi/wge
공식 코드Two-view Graph Neural Networks for Knowledge Graph Completion
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.