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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/KGQA/KGQA-datasets-generalization
공식 코드https://github.com/KKbeckang/LiGPT-Beta
공식 코드https://github.com/KRLabsOrg/LettuceDetect
공식 코드LettuceDetect: A Hallucination Detection Framework for RAG Applications
https://github.com/KRR-Oxford/OWL2Vec-Star
공식 코드https://github.com/KaiyueSun98/T2V-CompBench
공식 코드T2V-CompBench: A Comprehensive Benchmark for Compositional Text-to-video Generation
https://github.com/Kaylee0501/X-MLClass
공식 코드Open-world Multi-label Text Classification with Extremely Weak Supervision
https://github.com/Knowledge-aware-AI/GPTKB
공식 코드Enabling LLM Knowledge Analysis via Extensive Materialization
https://github.com/KnowledgeCaptureAndDiscovery/OBA
공식 코드OBA: An Ontology-Based Framework for Creating REST APIs for Knowledge Graphs
https://github.com/KokiKishimoto/cp_decomposition
공식 코드https://github.com/KokiKishimoto/cp_decomposition_alpha
공식 코드https://github.com/KordingLab/llm4teach-freetext-server
공식 코드A large language model-assisted education tool to provide feedback on open-ended responses
https://github.com/KotoHanon/LOCOCO
공식 코드Walk Wisely on Graph: Knowledge Graph Reasoning with Dual Agents via Efficient Guidance-Exploration
https://github.com/LAMDA-RL/CoLA
공식 코드https://github.com/LC1332/Chat-Haruhi-Suzumiya
공식 코드ChatHaruhi: Reviving Anime Character in Reality via Large Language Model
https://github.com/LHRLAB/HyperGraphRAG
공식 코드HyperGraphRAG: Retrieval-Augmented Generation with Hypergraph-Structured Knowledge Representation
https://github.com/LHY-24/KG-Compilation
공식 코드https://github.com/LINs-lab/M3
공식 코드https://github.com/LL-a-VO/VLLaVO
공식 코드https://github.com/LLLQAQFFF/360REA
공식 코드https://github.com/LLer0829/Measuring_Copyright_Risk_of_LLM
공식 코드Measuring Copyright Risks of Large Language Model via Partial Information Probing
https://github.com/Lancelot39/KGSF
공식 코드Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion
https://github.com/Leanna97/TSINR
공식 코드https://github.com/LeapLabTHU/diver-ct
공식 코드DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing Constraints
https://github.com/LemonNoel/ATransN
공식 코드An Adversarial Transfer Network for Knowledge Representation Learning
https://github.com/Li-Z-Q/DeepSolution
공식 코드https://github.com/LiGaoJi/MPLR
공식 코드An original model for multi-target learning of logical rules for knowledge graph reasoning
https://github.com/Libo1023/LEAP
공식 코드Large Language Models as Interpolated and Extrapolated Event Predictors
https://github.com/LinXueyuanStdio/EchoEA
공식 코드EchoEA: Echo Information between Entities and Relations for Entity Alignment
https://github.com/LiyingCheng95/EntityDescriptionGeneration
공식 코드ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
https://github.com/LongchaoDa/SegmentAsYouWish
공식 코드Segment as You Wish -- Free-Form Language-Based Segmentation for Medical Images
https://github.com/LuciusLan/Visual-RAG
공식 코드https://github.com/Luffy03/UniBiomed
공식 코드UniBiomed: A Universal Foundation Model for Grounded Biomedical Image Interpretation
https://github.com/METR/ai-rd-tasks
공식 코드RE-Bench: Evaluating frontier AI R&D capabilities of language model agents against human experts
https://github.com/MI-911/warm-start-framework
공식 코드MindReader: Recommendation over Knowledge Graph Entities with Explicit User Ratings
https://github.com/MIRALab-USTC/KG-TACT
공식 코드Topology-Aware Correlations Between Relations for Inductive Link Prediction in Knowledge Graphs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.