Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/GillesVandewiele/WalkExperiments
공식 코드Walk Extraction Strategies for Node Embeddings with RDF2Vec in Knowledge Graphs
https://github.com/Godheritage/SCOPE
공식 코드SCOPE: Sign Language Contextual Processing with Embedding from LLMs
https://github.com/Goedel-LM/Goedel-Prover
공식 코드Goedel-Prover: A Frontier Model for Open-Source Automated Theorem Proving
https://github.com/Guang000/Awesome-Dataset-Distillation
공식 코드https://github.com/GuanghuiFU/counselor_support
공식 코드https://github.com/HC-Guo/Owl
공식 코드https://github.com/HELL-TO-HEAVEN/KGE-CL
공식 코드KGE-CL: Contrastive Learning of Tensor Decomposition Based Knowledge Graph Embeddings
https://github.com/HKUST-KnowComp/ASER
공식 코드https://github.com/HKUST-KnowComp/FKGE
공식 코드https://github.com/HKUST-KnowComp/Pronoun-Coref-KG
공식 코드https://github.com/Hang422/causal-thought-graph
공식 코드Causal Graphs Meet Thoughts: Enhancing Complex Reasoning in Graph-Augmented LLMs
https://github.com/HanningChen/VLTP
공식 코드VLTP: Vision-Language Guided Token Pruning for Task-Oriented Segmentation
https://github.com/HaochenLiu2000/QAP
공식 코드Question-Aware Knowledge Graph Prompting for Enhancing Large Language Models
https://github.com/HaochenLiu2000/SAFER
공식 코드Few-shot Knowledge Graph Relational Reasoning via Subgraph Adaptation
https://github.com/HazyResearch/hyena-dna
공식 코드HyenaDNA: Long-Range Genomic Sequence Modeling at Single Nucleotide Resolution
https://github.com/HenryPengZou/Awesome-Human-Agent-Collaboration-Interaction-Systems
공식 코드https://github.com/Hippopotamus0308/SSTKG
공식 코드https://github.com/Holmes-Alan/FunnyNet-W
공식 코드FunnyNet-W: Multimodal Learning of Funny Moments in Videos in the Wild
https://github.com/HongzhiQ/SupervisedVsLLM-EfficacyEval
공식 코드https://github.com/HooRin/AuditWen
공식 코드https://github.com/HuihuiChyan/SelfEval
공식 코드Self-Evaluation of Large Language Model based on Glass-box Features
https://github.com/Hyun-Ryu/clover
공식 코드https://github.com/IAAR-Shanghai/Meta-Chunking
공식 코드Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perception
https://github.com/IAAR-Shanghai/QAEncoder
공식 코드QAEncoder: Towards Aligned Representation Learning in Question Answering System
https://github.com/IBM/Open-KG-canonicalization
공식 코드Open Knowledge Graphs Canonicalization using Variational Autoencoders
https://github.com/IBM/Retrieval-Enhanced-Transformer-Little
공식 코드https://github.com/IBM/RuDaS
공식 코드RuDaS: Synthetic Datasets for Rule Learning and Evaluation Tools
https://github.com/IBM/helm-enterprise-benchmark
공식 코드https://github.com/IBM/prompt-declaration-language
공식 코드https://github.com/IBM/retrieve-write-slot-filling
공식 코드https://github.com/IBM/wikicausal
공식 코드WikiCausal: Corpus and Evaluation Framework for Causal Knowledge Graph Construction
https://github.com/IDEA-Emdoor-Lab/UniTTS
공식 코드UniTTS: An end-to-end TTS system without decoupling of acoustic and semantic information
https://github.com/IDEA-FinAI/Simple-HHEA
공식 코드https://github.com/INDElab/rgvae
공식 코드Knowledge Generation -- Variational Bayes on Knowledge Graphs
https://github.com/INK-USC/CALM
공식 코드Pre-training Text-to-Text Transformers for Concept-centric Common Sense
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.