https://github.com/jjzha/fs1
공식 코드Scaling Reasoning can Improve Factuality in Large Language Models
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/johnnyjana730/MVIN
공식 코드https://github.com/joker-xii/clusterea
공식 코드ClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similarities
https://github.com/jonathanschuchart/eager
공식 코드EAGER: Embedding-Assisted Entity Resolution for Knowledge Graphs
https://github.com/jrbn/kognac
공식 코드https://github.com/jrbn/vlog
공식 코드Column-Oriented Datalog Materialization for Large Knowledge Graphs (Extended Technical Report)
https://github.com/juliagast/tgb2
공식 코드TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
https://github.com/junkangwu/DisenKGAT
공식 코드DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network
https://github.com/justinhjy1004/fairuselegalbot
공식 코드Incorporating Legal Structure in Retrieval-Augmented Generation: A Case Study on Copyright Fair Use
https://github.com/juyeonnn/kgmel
공식 코드https://github.com/jwzhanggy/Graph_Toolformer
공식 코드Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT
https://github.com/kabongosalomon/task-dataset-metric-nli-extraction
공식 코드https://github.com/kalifadan/GOProteinGNN
공식 코드GOProteinGNN: Leveraging Protein Knowledge Graphs for Protein Representation Learning
https://github.com/kasnerz/rel2text
공식 코드Mind the Labels: Describing Relations in Knowledge Graphs With Pretrained Models
https://github.com/kbogas/pam_cbms
공식 코드Analysing Biomedical Knowledge Graphs using Prime Adjacency Matrices
https://github.com/kcacozhang/lgre
공식 코드Learning Granularity Representation for Temporal Knowledge Graph Completion
https://github.com/kevinj22/CNRec
공식 코드Content based News Recommendation via Shortest Entity Distance over Knowledge Graphs
https://github.com/kgrl2021/submission-one
공식 코드A Study on Knowledge Graph Embeddings and Graph Neural Networks for Web Of Things
https://github.com/kingsaint/InductiveExplainableLinkPrediction
공식 코드Explainable Link Prediction for Emerging Entities in Knowledge Graphs
https://github.com/kingsaint/Open-vocabulary-entity-type-description
공식 코드Generating Fine-Grained Open Vocabulary Entity Type Descriptions
https://github.com/kingsaint/Wikidata-Descriptions
공식 코드Be Concise and Precise: Synthesizing Open-Domain Entity Descriptions from Facts
https://github.com/kjh9503/caqr
공식 코드https://github.com/kkteru/grail
공식 코드https://github.com/kmswin1/comdense
공식 코드https://github.com/knowledge-graphs-tutorial/examples
공식 코드https://github.com/knowsys/2022-iswc-reliances
공식 코드https://github.com/knowsys/nemo
공식 코드https://github.com/kolejnyy/ANYCQ
공식 코드https://github.com/kracr/rcone-qa-mmkg
공식 코드RConE: Rough Cone Embedding for Multi-Hop Logical Query Answering on Multi-Modal Knowledge Graphs
https://github.com/kramerlab/focusedretriever
공식 코드Focus, Merge, Rank: Improved Question Answering Based on Semi-structured Knowledge Bases
https://github.com/krr-oxford/boxsquaredel
공식 코드https://github.com/krystalan/RAGtrans
공식 코드Retrieval-Augmented Machine Translation with Unstructured Knowledge
https://github.com/kse-eleven/makged
공식 코드https://github.com/ktr0921/tac
공식 코드A Minimal Approach for Natural Language Action Space in Text-based Games
https://github.com/kuanglab/LowrankTLP
공식 코드Scalable Label Propagation for Multi-relational Learning on the Tensor Product of Graphs
https://github.com/kxinwang2023/enco
공식 코드Improving the Robustness of Knowledge-Grounded Dialogue via Contrastive Learning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.