https://github.com/opendatalab/pm4bench
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
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/parajain/structscribe
Scalable Micro-planned Generation of Discourse from Structured Data
https://github.com/parkererickson/crunchBaseGraph
https://github.com/pengboci/graphrag-survey
https://github.com/phunterlau/paper_without_code/tree/main/examples/PoG/
Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs
https://github.com/phunterlau/paper_without_code/tree/main/examples/community-rag
https://github.com/pminervini/kgreasoning
https://github.com/pyg-team/pytorch_geometric/blob/master/torch_geometric/nn/kge/rotate.py
RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
https://github.com/rahmanidashti/acqsurvey
https://github.com/raphaelsty/mkb
Inductive Entity Representations from Text via Link Prediction
https://github.com/rothamsted/rdf2pg
https://github.com/rucaibox/safe
QA-GNN: Reasoning with Language Models and Knowledge Graphs for Question Answering
https://github.com/rudongyu/logire
RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
https://github.com/ruotianluo/zsl-gcn-pth
Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs
https://github.com/samleoqh/MultiModNet
https://github.com/security-force-monitor/sfm-graph-extractor
https://github.com/seeyourmind/tkgelib
HittER: Hierarchical Transformers for Knowledge Graph Embeddings
https://github.com/semantic-systems/NLIWOD
https://github.com/shamim-hussain/egt
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
https://github.com/sheepover96/ProjE.torch
https://github.com/shijx12/kqapro_baselines
https://github.com/sib-swiss/sparql-examples-utils
https://github.com/sid-sundrani/differentiable-kb-qa
Expanding End-to-End Question Answering on Differentiable Knowledge Graphs with Intersection
https://github.com/smoothnlp/SmoothNLP
https://github.com/snap-stanford/KGReasoning
https://github.com/snap-stanford/neural-subgraph-learning-gnn
https://github.com/snap-stanford/ogb/tree/master/examples/linkproppred/citation2
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/linkproppred/collab
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/linkproppred/ddi
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/linkproppred/ppa
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/arxiv
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/mag
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/papers100M
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/products
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/snap-stanford/ogb/tree/master/examples/nodeproppred/proteins
Open Graph Benchmark: Datasets for Machine Learning on Graphs
https://github.com/songzeceng/KGNNLS_DEMO
Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.