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Large Language Model
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/nicyscaria/AEQG-MCQ-Distractors-Physics
공식 코드https://github.com/nidryen-zh/privacyannotation
공식 코드Automated Privacy Information Annotation in Large Language Model Interactions
https://github.com/nidryen-zh/questionerawareresponder
공식 코드Personalized LLM for Generating Customized Responses to the Same Query from Different Users
https://github.com/nightdessert/retrieval_head
공식 코드Retrieval Head Mechanistically Explains Long-Context Factuality
https://github.com/nikivanstein/LLaMEA
공식 코드LLaMEA: A Large Language Model Evolutionary Algorithm for Automatically Generating Metaheuristics
https://github.com/nikolamilosevic86/verif.ai
공식 코드https://github.com/nil-zhuang/efficientrag-official
공식 코드EfficientRAG: Efficient Retriever for Multi-Hop Question Answering
https://github.com/ninecl/dekg-ilp
공식 코드Disconnected Emerging Knowledge Graph Oriented Inductive Link Prediction
https://github.com/ninibymilk/pmf-mmea
공식 코드Progressively Modality Freezing for Multi-Modal Entity Alignment
https://github.com/ninjatech-ai/mple
공식 코드Multi-Programming Language Ensemble for Code Generation in Large Language Model
https://github.com/niraj17singh/linklogic
공식 코드LinkLogic: A New Method and Benchmark for Explainable Knowledge Graph Predictions
https://github.com/nishchalprasad/mesc
공식 코드https://github.com/niteshroyal/solvinghardanalogyquestions
공식 코드Solving Hard Analogy Questions with Relation Embedding Chains
https://github.com/niuchuangnn/vllm_structure
공식 코드https://github.com/nju-pcalab/rag-diffusion
공식 코드Region-Aware Text-to-Image Generation via Hard Binding and Soft Refinement
https://github.com/nju-websoft/AliNet
공식 코드Knowledge Graph Alignment Network with Gated Multi-hop Neighborhood Aggregation
https://github.com/nju-websoft/CR2
공식 코드Enriching Documents with Compact, Representative, Relevant Knowledge Graphs
https://github.com/nju-websoft/DeepLENS
공식 코드https://github.com/nju-websoft/HyperKA
공식 코드Knowledge Association with Hyperbolic Knowledge Graph Embeddings
https://github.com/nju-websoft/KG-ICL
공식 코드A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoning
https://github.com/nju-websoft/KG2RAG
공식 코드https://github.com/nju-websoft/MultiKE
공식 코드https://github.com/nju-websoft/OpenEA
공식 코드A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs
https://github.com/nju-websoft/RGRec
공식 코드https://github.com/nju-websoft/RSN
공식 코드Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
https://github.com/nju-websoft/TransEdge
공식 코드TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphs
https://github.com/nju-websoft/cca
공식 코드Knowledge Graph Error Detection with Contrastive Confidence Adaption
https://github.com/nju-websoft/contea
공식 코드Facing Changes: Continual Entity Alignment for Growing Knowledge Graphs
https://github.com/nju-websoft/daakg
공식 코드Deep Active Alignment of Knowledge Graph Entities and Schemata
https://github.com/nju-websoft/epr-kgqa
공식 코드Enhancing Complex Question Answering over Knowledge Graphs through Evidence Pattern Retrieval
https://github.com/nju-websoft/eventea
공식 코드EventEA: Benchmarking Entity Alignment for Event-centric Knowledge Graphs
https://github.com/nju-websoft/exea
공식 코드Generating Explanations to Understand and Repair Embedding-based Entity Alignment
https://github.com/nju-websoft/kire
공식 코드Enhancing Document-level Relation Extraction by Entity Knowledge Injection
https://github.com/nju-websoft/knowla
공식 코드KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptation
https://github.com/nju-websoft/lkge
공식 코드Lifelong Embedding Learning and Transfer for Growing Knowledge Graphs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.