Inductive knowledge graph completion
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/MurtyShikhar/KBI
Joint Matrix-Tensor Factorization for Knowledge Base Inference
https://github.com/NUS-HPC-AI-Lab/VideoSys
https://github.com/NVIDIA/NeMo-Skills
OpenMathInstruct-2: Accelerating AI for Math with Massive Open-Source Instruction Data
https://github.com/NamyongPark/EvoKG
https://github.com/OpenMOSS/AnyGPT
AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling
https://github.com/PAIR-code/llm-comparator
https://github.com/PKD667/political-alignement
https://github.com/PKU-YuanGroup/MoE-LLaVA
Video-LLaVA: Learning United Visual Representation by Alignment Before Projection
https://github.com/PaddlePaddle/PaddleRec/tree/master/models/match/kim
Personalized News Recommendation with Knowledge-aware Interactive Matching
https://github.com/Peter7Yao/RNM
Relation-Aware Neighborhood Matching Model for Entity Alignment
https://github.com/Phoenix1327/ML-ZSL
Multi-Label Zero-Shot Learning with Structured Knowledge Graphs
https://github.com/PierreSenellart/theoremkb
Extracting Definienda in Mathematical Scholarly Articles with Transformers
https://github.com/Pointcept/GPT4Point
https://github.com/QLaHPD/Dimension-Insensitive-Euclidean-Metric-
https://github.com/Qiyuan-Ge/PaintMind
Muse: Text-To-Image Generation via Masked Generative Transformers
https://github.com/QustKcz/relational-GCN
https://github.com/QwenLM/Qwen2.5-Omni
https://github.com/ROCm/flash-attention
Efficient Memory Management for Large Language Model Serving with PagedAttention
https://github.com/RUCAIBox/KGSF
Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
https://github.com/RUCAIBox/R1-Searcher
ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding
https://github.com/RUCDM/KB4Rec
https://github.com/RUCDM/KB4Rec/tree/master/Projects/UPGAN
https://github.com/Resurgamm/AGP
https://github.com/RichardHGL/UPGAN
https://github.com/RikiyaT/LARA
Large language models can accurately predict searcher preferences
https://github.com/SSE-PT/SSE-PT
Stochastic Shared Embeddings: Data-driven Regularization of Embedding Layers
https://github.com/STIInnsbruck/kgs
Duplication Detection in Knowledge Graphs: Literature and Tools
https://github.com/SandraSchaftner/orkg_property_extraction_using_gpt-3.5
https://github.com/SejeongPark8354/MforDrugDev
A Review of Biomedical Datasets Relating to Drug Discovery: A Knowledge Graph Perspective
https://github.com/ShubhamKumarNigam/NyayaAnumana-and-INLegalLlama
https://github.com/SmartDataAnalytics/PyKEEN
PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings
https://github.com/SparkZu/RadioLLM
https://github.com/Spracks/PackageHallucination
https://github.com/Stanford-AIMI/CheXagent
A Vision-Language Foundation Model to Enhance Efficiency of Chest X-ray Interpretation
https://github.com/SteveTANTAN/PoG
Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.