https://github.com/DeepGraphLearning/NBFNet
공식 코드Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Prediction
Papers with Code 아카이브
Knowledge Graphs
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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/DeepGraphLearning/RNNLogic
공식 코드RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs
https://github.com/DeepGraphLearning/ULTRA
공식 코드https://github.com/DeepSoftwareAnalytics/CoSQA_Plus
공식 코드CoSQA+: Pioneering the Multi-Choice Code Search Benchmark with Test-Driven Agents
https://github.com/DexterZeng/CEA
공식 코드https://github.com/DexterZeng/CEAFF
공식 코드Reinforcement Learning based Collective Entity Alignment with Adaptive Features
https://github.com/DexterZeng/DAT
공식 코드https://github.com/DexterZeng/UEA
공식 코드Towards Entity Alignment in the Open World: An Unsupervised Approach
https://github.com/DimitrisAlivas/StarQE
공식 코드https://github.com/DominikFilipiak/KGTN-ens
공식 코드KGTN-ens: Few-Shot Image Classification with Knowledge Graph Ensembles
https://github.com/Dongzhikang/MuseChat-dataset
공식 코드MuseChat: A Conversational Music Recommendation System for Videos
https://github.com/EagleW/PaperRobot
공식 코드PaperRobot: Incremental Draft Generation of Scientific Ideas
https://github.com/EarlFan/ChatCFD
공식 코드ChatCFD: an End-to-End CFD Agent with Domain-specific Structured Thinking
https://github.com/Ebiquity/KGFP
공식 코드Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization
https://github.com/EdenBelouadah/class-incremental-learning
공식 코드ScaIL: Classifier Weights Scaling for Class Incremental Learning
https://github.com/EleutherAI/math-lm
공식 코드https://github.com/Elric2718/Bayes_Embedding
공식 코드https://github.com/EmergenceAI/dartboard
공식 코드https://github.com/EncryptedBinary/Meta_analysis
공식 코드Empowering Meta-Analysis: Leveraging Large Language Models for Scientific Synthesis
https://github.com/EpistasisLab/pennai
공식 코드Evaluating recommender systems for AI-driven biomedical informatics
https://github.com/EruM16/Attention-Seeker
공식 코드Attention-Seeker: Dynamic Self-Attention Scoring for Unsupervised Keyphrase Extraction
https://github.com/ErxinYu/CoSafe-Dataset
공식 코드CoSafe: Evaluating Large Language Model Safety in Multi-Turn Dialogue Coreference
https://github.com/EsmaeilNarimissa/RAG-Retrieval-Analysis
공식 코드https://github.com/EthanLifeGreat/SuDoSys
공식 코드Structured Dialogue System for Mental Health: An LLM Chatbot Leveraging the PM+ Guidelines
https://github.com/EvalCrafter/EvalCrafter
공식 코드EvalCrafter: Benchmarking and Evaluating Large Video Generation Models
https://github.com/EvoNexusX/Graph-Retrieval-Augmented-Trustworthiness-Reasoning
공식 코드GRATR: Zero-Shot Evidence Graph Retrieval-Augmented Trustworthiness Reasoning
https://github.com/Ezharjan/AutoSceneGen
공식 코드Generating Traffic Scenarios via In-Context Learning to Learn Better Motion Planner
https://github.com/FKIRSTE/emnlp2024-personalized-meeting-sum
공식 코드https://github.com/FaisalQarah/EgyBERT
공식 코드EgyBERT: A Large Language Model Pretrained on Egyptian Dialect Corpora
https://github.com/Fangkang515/CE3D
공식 코드https://github.com/FeiLiu36/LLM4MOEA
공식 코드Large Language Model for Multi-objective Evolutionary Optimization
https://github.com/FelixFrohnertDB/arxiv_nlp
공식 코드Discovering emergent connections in quantum physics research via dynamic word embeddings
https://github.com/Flossiee/HonestyLLM
공식 코드HonestLLM: Toward an Honest and Helpful Large Language Model
https://github.com/FomalhautB/KM-BART-ACL
공식 코드KM-BART: Knowledge Enhanced Multimodal BART for Visual Commonsense Generation
https://github.com/ForzaETH/LLMxRobot
공식 코드Enhancing Autonomous Driving Systems with On-Board Deployed Large Language Models
https://github.com/FoundationVision/Groma
공식 코드Groma: Localized Visual Tokenization for Grounding Multimodal Large Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.