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Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/BillChan226/AgentPoison
공식 코드AgentPoison: Red-teaming LLM Agents via Poisoning Memory or Knowledge Bases
https://github.com/BioMedicalBigDataMiningLab/TDRC
공식 코드https://github.com/BorealisAI/DE-SimplE
공식 코드Diachronic Embedding for Temporal Knowledge Graph Completion
https://github.com/BorealisAI/OOS-KGE
공식 코드Out-of-Sample Representation Learning for Multi-Relational Graphs
https://github.com/BriansIDP/video-SALMONN-o1
공식 코드video-SALMONN-o1: Reasoning-enhanced Audio-visual Large Language Model
https://github.com/ByungKwanLee/CoLLaVO
공식 코드https://github.com/ByunghweeLee-IU/Belief-Embedding
공식 코드A semantic embedding space based on large language models for modelling human beliefs
https://github.com/CCIIPLab/KGTN
공식 코드Knowledge Enhanced Multi-intent Transformer Network for Recommendation
https://github.com/CLARIN-PL/PUGG
공식 코드Developing PUGG for Polish: A Modern Approach to KBQA, MRC, and IR Dataset Construction
https://github.com/CSJianYang/Multilingual-Multimodal-NLP/tree/main/MT4CrossOIE
공식 코드MT4CrossOIE: Multi-stage Tuning for Cross-lingual Open Information Extraction
https://github.com/CatIIIIIIII/veriseek
공식 코드Large Language Model for Verilog Generation with Code-Structure-Guided Reinforcement Learning
https://github.com/Cavendish518/LE-Nav
공식 코드https://github.com/Chandrahasd/OKGIT
공식 코드OKGIT: Open Knowledge Graph Link Prediction with Implicit Types
https://github.com/Chat-3D/Chat-3D
공식 코드Chat-3D: Data-efficiently Tuning Large Language Model for Universal Dialogue of 3D Scenes
https://github.com/ChengshuaiZhao0/SCALE
공식 코드https://github.com/ChenxiLiu-HNU/ST-LLM
공식 코드Spatial-Temporal Large Language Model for Traffic Prediction
https://github.com/China-UK-ZSL/ZS-F-VQA
공식 코드https://github.com/Comcast/llm-stability
공식 코드https://github.com/CompNet/conivel
공식 코드Learning to Rank Context for Named Entity Recognition Using a Synthetic Dataset
https://github.com/CunchaoZ/CyGNet
공식 코드Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
https://github.com/CyberAgentAILab/diverse-mbr
공식 코드Generating Diverse and High-Quality Texts by Minimum Bayes Risk Decoding
https://github.com/DM1122/LLMSat
공식 코드LLMSat: A Large Language Model-Based Goal-Oriented Agent for Autonomous Space Exploration
https://github.com/DM2-ND/MoKGE
공식 코드Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts
https://github.com/Dakantz/OnSET
공식 코드https://github.com/Daniel-Gong/ChatGPT_WM
공식 코드https://github.com/DataScienceUIBK/Rankify
공식 코드https://github.com/Deagogishvili/chapter-multi-task
공식 코드PatchProt: Hydrophobic patch prediction using protein foundation models
https://github.com/DeepGraphLearning/GNN-QE
공식 코드Neural-Symbolic Models for Logical Queries on Knowledge Graphs
https://github.com/DeepGraphLearning/KnowledgeGraphEmbedding
공식 코드RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
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 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.