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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/yinzhangyue/eot
공식 코드Exchange-of-Thought: Enhancing Large Language Model Capabilities through Cross-Model Communication
https://github.com/yiqingxyq/codebenchgen
공식 코드CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks
https://github.com/yisuanwang/soulstyler
공식 코드Soulstyler: Using Large Language Model to Guide Image Style Transfer for Target Object
https://github.com/yiveen/syntheticdatafeasibility
공식 코드Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data
https://github.com/yixiangch/mrd-rag
공식 코드MRD-RAG: Enhancing Medical Diagnosis with Multi-Round Retrieval-Augmented Generation
https://github.com/yixuantt/MultiHop-RAG
공식 코드MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries
https://github.com/yizhilll/transher
공식 코드TranSHER: Translating Knowledge Graph Embedding with Hyper-Ellipsoidal Restriction
https://github.com/yjeugenia/maferw
공식 코드MaFeRw: Query Rewriting with Multi-Aspect Feedbacks for Retrieval-Augmented Large Language Models
https://github.com/yjiangcm/lion
공식 코드Lion: Adversarial Distillation of Proprietary Large Language Models
https://github.com/yjsoh/youra
공식 코드You Only Use Reactive Attention Slice For Long Context Retrieval
https://github.com/ykumards/eclip
공식 코드Improving Medical Multi-modal Contrastive Learning with Expert Annotations
https://github.com/ykzhang721/COG
공식 코드https://github.com/ym689/rec_icl
공식 코드Real-Time Personalization for LLM-based Recommendation with Customized In-Context Learning
https://github.com/ymoslem/adaptive-mt-llm-fine-tuning
공식 코드Fine-tuning Large Language Models for Adaptive Machine Translation
https://github.com/yoadtew/zero-shot-image-to-text
공식 코드ZeroCap: Zero-Shot Image-to-Text Generation for Visual-Semantic Arithmetic
https://github.com/yoda-lab/dialectical-reconciliation-with-structured-argumentation
공식 코드Dialectical Reconciliation via Structured Argumentative Dialogues
https://github.com/yoda-lab/persona
공식 코드https://github.com/yohanjo/kenli
공식 코드Knowledge-Enhanced Evidence Retrieval for Counterargument Generation
https://github.com/yongaifadian1/Dynamic-Parameter-Memory_DPM
공식 코드https://github.com/yongchao98/promst
공식 코드https://github.com/yosukehiguchi/espnet
공식 코드https://github.com/you68681/lpw
공식 코드Planning-Driven Programming: A Large Language Model Programming Workflow
https://github.com/youngdubbydu/llm-agent-optimization
공식 코드A Survey on the Optimization of Large Language Model-based Agents
https://github.com/youngerous/qtree
공식 코드Learning to Explore and Select for Coverage-Conditioned Retrieval-Augmented Generation
https://github.com/youngseungjeon/ragppi
공식 코드RAGPPI: RAG Benchmark for Protein-Protein Interactions in Drug Discovery
https://github.com/ys-feng/DemoGraph
공식 코드Democratizing Large Language Model-Based Graph Data Augmentation via Latent Knowledge Graphs
https://github.com/ysh-1998/csrec
공식 코드Common Sense Enhanced Knowledge-based Recommendation with Large Language Model
https://github.com/ysh-1998/lrd
공식 코드Sequential Recommendation with Latent Relations based on Large Language Model
https://github.com/ysunbp/taxoglimpse
공식 코드https://github.com/ysyushi/HyperMine
공식 코드https://github.com/ytomc/autoassumpdl
공식 코드https://github.com/ytongxie/pairaug
공식 코드PairAug: What Can Augmented Image-Text Pairs Do for Radiology?
https://github.com/ytyz1307zzh/minimally_edited_questions
공식 코드https://github.com/yu-rp/dimple
공식 코드Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding
https://github.com/yu-rp/visualperceptiontoken
공식 코드Introducing Visual Perception Token into Multimodal Large Language Model
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.