Papers with Code 아카이브
Knowledge Graphs
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
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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/Fangyin1994/KCL
https://github.com/Flajt/Veritas
https://github.com/FoundationVision/Infinity
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
https://github.com/FreedomIntelligence/BlenderLLM
https://github.com/FreedomIntelligence/PlatoLM
PlatoLM: Teaching LLMs in Multi-Round Dialogue via a User Simulator
https://github.com/FunAudioLLM/ThinkSound
https://github.com/GLUS-video/GLUS
GLUS: Global-Local Reasoning Unified into A Single Large Language Model for Video Segmentation
https://github.com/Garrafao/WUGs
DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages
https://github.com/GitF82/NLP-Embeddings-Protoformer-Paper
https://github.com/Grecil/Corrective-RAG
https://github.com/Hasegawa-lab-JAIST/LI_JINGHONG_Hierarchical-Tree-structured-Knowledge-Graph-For-Academic-Insight-Survey
Hierarchical Tree-structured Knowledge Graph For Academic Insight Survey
https://github.com/HazyResearch/KGEmb
https://github.com/HectorHHZ/Sparse_Matrix_Tuning
https://github.com/HettyPatel/TRAWL
TRAWL: Tensor Reduced and Approximated Weights for Large Language Models
https://github.com/Hunter-DDM/InvTransE-and-InvRotatE
https://github.com/Hyeongkeun/LAVCap
LAVCap: LLM-based Audio-Visual Captioning using Optimal Transport
https://github.com/ICT-GoKnow/KnowCoder
KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction
https://github.com/Jacfger/simple-stuffs
Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddings
https://github.com/JesusCarr/JARVIS
https://github.com/JiabenLi/rgcn_paddlepaddle
https://github.com/JingfenQiao/ColPali-Reproducibility
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/Jl-wei/ai-gen-ui
https://github.com/JohnKurian/R2D2
https://github.com/JudyYe/zero-shot-gcn
Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs
https://github.com/KXY-PUBLIC/NASE
Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs
https://github.com/KastanDay/video-pretrained-transformer
https://github.com/KaveeshaSIlva/Baseline-FYP
PathVQA: 30000+ Questions for Medical Visual Question Answering
https://github.com/KaveeshaSIlva/PathVQA
PathVQA: 30000+ Questions for Medical Visual Question Answering
https://github.com/LB0828/conve_reproduce
https://github.com/LaVi-Lab/Video-3D-LLM
Learning from Videos for 3D World: Enhancing MLLMs with 3D Vision Geometry Priors
https://github.com/Leeroo-AI/mergoo
https://github.com/LiuHuijie6410/OmniDish
Omni-Dish: Photorealistic and Faithful Image Generation and Editing for Arbitrary Chinese Dishes
https://github.com/LunaBlack/KGAT-pytorch
https://github.com/MARMOTatZJU/ZSLPR-TIANCHI
Zero-shot Recognition via Semantic Embeddings and Knowledge Graphs
https://github.com/MIRALab-USTC/GraphAKD
Rethinking Graph Convolutional Networks in Knowledge Graph Completion
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.