Retrieval-augmented Generation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/richard-peng-xia/mmed-rag
공식 코드MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models
https://github.com/richard-peng-xia/rule
공식 코드RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models
https://github.com/riedlerm/multimodal_rag_for_industry
공식 코드Beyond Text: Optimizing RAG with Multimodal Inputs for Industrial Applications
https://github.com/ritaranx/collab-rag
공식 코드https://github.com/rmit-ir/GRAG-LiveRAG
공식 코드https://github.com/robertlakatos/ragvsfn
공식 코드https://github.com/ruc-nlpir/flashrag
공식 코드FlashRAG: A Modular Toolkit for Efficient Retrieval-Augmented Generation Research
https://github.com/ruc-nlpir/omnieval
공식 코드OmniEval: An Omnidirectional and Automatic RAG Evaluation Benchmark in Financial Domain
https://github.com/rucaibox/r1-searcher-plus
공식 코드R1-Searcher++: Incentivizing the Dynamic Knowledge Acquisition of LLMs via Reinforcement Learning
https://github.com/rucaibox/rear
공식 코드REAR: A Relevance-Aware Retrieval-Augmented Framework for Open-Domain Question Answering
https://github.com/rucaibox/simpledeepsearcher
공식 코드SimpleDeepSearcher: Deep Information Seeking via Web-Powered Reasoning Trajectory Synthesis
https://github.com/rui9812/knowtrace
공식 코드KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge Tracing
https://github.com/run-llama/llama_index
공식 코드https://github.com/ryuichi-sumida/lufy
공식 코드https://github.com/sa4s-serc/llm4adr
공식 코드https://github.com/salesforceairesearch/contextualjudgebench
공식 코드Does Context Matter? ContextualJudgeBench for Evaluating LLM-based Judges in Contextual Settings
https://github.com/salesforceairesearch/faitheval
공식 코드https://github.com/sam-rag/sam_rag
공식 코드https://github.com/samyateia/bioasq2024
공식 코드https://github.com/sarashs/fpga_agi
공식 코드SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation
https://github.com/sarthak-choudhary/stealthy_attacks_against_rag
공식 코드Through the Stealth Lens: Rethinking Attacks and Defenses in RAG
https://github.com/sarus-tech/dp-rag
공식 코드https://github.com/saturnmars/derivingstructuredinsightsfromsustainabilityreportsvialargelanguagemodels
공식 코드Glitter or Gold? Deriving Structured Insights from Sustainability Reports via Large Language Models
https://github.com/sayantan11995/wikipedia_enrichment
공식 코드https://github.com/sciknoworg/ontoaligner
공식 코드OntoAligner: A Comprehensive Modular and Robust Python Toolkit for Ontology Alignment
https://github.com/scut-dlvclab/tonggu-llm
공식 코드TongGu: Mastering Classical Chinese Understanding with Knowledge-Grounded Large Language Models
https://github.com/sding11/RAG-VR
공식 코드RAG-VR: Leveraging Retrieval-Augmented Generation for 3D Question Answering in VR Environments
https://github.com/se-sic/icse_model_completion
공식 코드https://github.com/se-sic/ramc_model_completion
공식 코드https://github.com/seasonyao/noteaid-readme
공식 코드README: Bridging Medical Jargon and Lay Understanding for Patient Education through Data-Centric NLP
https://github.com/sefeoglu/rag4re
공식 코드https://github.com/selbeltagy/arragexperiments
공식 코드https://github.com/semantic-systems/nfdi-search-engine-chatbot
공식 코드Scholarly Question Answering using Large Language Models in the NFDI4DataScience Gateway
https://github.com/semanto-mondal/A-RAG-Augmented-YOLOv8-Framework
공식 코드https://github.com/seohyunwoo-0407/gar
공식 코드출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.