https://github.com/d-gurgurov/Injecting-Commonsense-Knowledge-into-LLMs
공식 코드Adapting Multilingual LLMs to Low-Resource Languages with Knowledge Graphs via Adapters
Papers with Code 아카이브
Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/d3mlab/cr-lt-kgqa
공식 코드https://github.com/dadelani/sib-200
공식 코드https://github.com/daehuikim/WikiOFGraph
공식 코드https://github.com/daiquocnguyen/CapsE
공식 코드A Capsule Network-based Embedding Model for Knowledge Graph Completion and Search Personalization
https://github.com/daiquocnguyen/GNN-NoGE
공식 코드Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction
https://github.com/daiquocnguyen/QGNN
공식 코드https://github.com/daiquocnguyen/QuatRE
공식 코드QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings
https://github.com/daiquocnguyen/R-MeN
공식 코드A Relational Memory-based Embedding Model for Triple Classification and Search Personalization
https://github.com/dair-iitd/KGC-Ensemble
공식 코드DynaSemble: Dynamic Ensembling of Textual and Structure-Based Models for Knowledge Graph Completion
https://github.com/dair-iitd/NS-KGC-AUG
공식 코드Simple Augmentations of Logical Rules for Neuro-Symbolic Knowledge Graph Completion
https://github.com/dair-iitd/kbi
공식 코드Joint Matrix-Tensor Factorization for Knowledge Base Inference
https://github.com/dair-iitd/tkbi
공식 코드Temporal Knowledge Base Completion: New Algorithms and Evaluation Protocols
https://github.com/damo-nlp-sg/chain-of-knowledge
공식 코드https://github.com/damo-nlp-sg/llm-r2
공식 코드LLM-R2: A Large Language Model Enhanced Rule-based Rewrite System for Boosting Query Efficiency
https://github.com/dandoge/palm
공식 코드https://github.com/dangxingyu/rnn-icrag
공식 코드RNNs are not Transformers (Yet): The Key Bottleneck on In-context Retrieval
https://github.com/daniel-chin/flute-x-gpt
공식 코드https://github.com/daniel-gong/chatgpt-wm
공식 코드https://github.com/danieladam2001/llm-based-validation
공식 코드Traceable LLM-based validation of statements in knowledge graphs
https://github.com/danielfperez/castillo
공식 코드CASTILLO: Characterizing Response Length Distributions of Large Language Models
https://github.com/danielkty/debiasing-rag
공식 코드https://github.com/danilo-dessi/skg
공식 코드https://github.com/daod/spring
공식 코드https://github.com/daromog/q-vid
공식 코드Question-Instructed Visual Descriptions for Zero-Shot Video Question Answering
https://github.com/darthreca/segmentation-losses-nlp
공식 코드Beyond Accuracy Optimization: Computer Vision Losses for Large Language Model Fine-Tuning
https://github.com/data-engineering-and-semantics/openkgbiblio
공식 코드https://github.com/datarobot/syftr
공식 코드https://github.com/datascienceuibk/triviahg
공식 코드TriviaHG: A Dataset for Automatic Hint Generation from Factoid Questions
https://github.com/davendw49/PK-Chat
공식 코드PK-Chat: Pointer Network Guided Knowledge Driven Generative Dialogue Model
https://github.com/david-li0406/contextulization-distillation
공식 코드Contextualization Distillation from Large Language Model for Knowledge Graph Completion
https://github.com/davidheineman/category-fluency
공식 코드https://github.com/davidlamprecht/autordf2gml
공식 코드AutoRDF2GML: Facilitating RDF Integration in Graph Machine Learning
https://github.com/davidlamprecht/linkedpaperswithcode
공식 코드Linked Papers With Code: The Latest in Machine Learning as an RDF Knowledge Graph
https://github.com/davidlamprecht/rdf-gnn-recommendation
공식 코드Bridging RDF Knowledge Graphs with Graph Neural Networks for Semantically-Rich Recommender Systems
https://github.com/davidlvxin/TransC
공식 코드Differentiating Concepts and Instances for Knowledge Graph Embedding
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.