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Retrieval-augmented Generation
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코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/tsinghua-dhy/edc-2-rag
공식 코드Efficient Dynamic Clustering-Based Document Compression for Retrieval-Augmented-Generation
https://github.com/tupyp7180/cft-rag-2025
공식 코드CFT-RAG: An Entity Tree Based Retrieval Augmented Generation Algorithm With Cuckoo Filter
https://github.com/tychenn/aqua
공식 코드Safeguarding Multimodal Knowledge Copyright in the RAG-as-a-Service Environment
https://github.com/uc-cdis/label-boosted-RAG-for-RRG
공식 코드LaB-RAG: Label Boosted Retrieval Augmented Generation for Radiology Report Generation
https://github.com/ucscirkm/sim-rag
공식 코드Knowing You Don't Know: Learning When to Continue Search in Multi-round RAG through Self-Practicing
https://github.com/ulab-uiuc/gor
공식 코드Graph of Records: Boosting Retrieval Augmented Generation for Long-context Summarization with Graphs
https://github.com/ulab-uiuc/gwm
공식 코드https://github.com/umass-ml4ed/syllabusqa
공식 코드https://github.com/ustcagi/crag-in-kdd-cup2024
공식 코드https://github.com/ustcagi/pruningrag
공식 코드Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study
https://github.com/ustcagi/rag-x
공식 코드Multi-Source Knowledge Pruning for Retrieval-Augmented Generation: A Benchmark and Empirical Study
https://github.com/vahidaz/llamarec-lkg-rag
공식 코드LlamaRec-LKG-RAG: A Single-Pass, Learnable Knowledge Graph-RAG Framework for LLM-Based Ranking
https://github.com/vasiliskatr/faaf
공식 코드FaaF: Facts as a Function for the evaluation of generated text
https://github.com/vectara/faithbench
공식 코드FaithBench: A Diverse Hallucination Benchmark for Summarization by Modern LLMs
https://github.com/vectara/mirage-bench
공식 코드MIRAGE-Bench: Automatic Multilingual Benchmark Arena for Retrieval-Augmented Generation Systems
https://github.com/vectorinstitute/fed-rag
공식 코드FedRAG: A Framework for Fine-Tuning Retrieval-Augmented Generation Systems
https://github.com/verdurechen/sos-retrieval-loop
공식 코드https://github.com/vidminas/socialgenpod
공식 코드https://github.com/vinairesearch/whoqa
공식 코드Who's Who: Large Language Models Meet Knowledge Conflicts in Practice
https://github.com/vinsontang1/slidecoder
공식 코드SlideCoder: Layout-aware RAG-enhanced Hierarchical Slide Generation from Design
https://github.com/vision-cair/dochaystacks
공식 코드Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ Documents
https://github.com/vistec-ai/nitibench
공식 코드NitiBench: A Comprehensive Studies of LLM Frameworks Capabilities for Thai Legal Question Answering
https://github.com/visual-haystacks/vhs_benchmark
공식 코드Visual Haystacks: A Vision-Centric Needle-In-A-Haystack Benchmark
https://github.com/weaidb/awesome-data-llm
공식 코드https://github.com/weaidb/awsome-data-llm
공식 코드https://github.com/webeng/llm_knowledge_gap_finder
공식 코드Harnessing Retrieval-Augmented Generation (RAG) for Uncovering Knowledge Gaps
https://github.com/webis-de/scolia25-xsum
공식 코드Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature Summarization
https://github.com/webis-de/sigir25-rag-crowdsourcing
공식 코드https://github.com/weizhepei/instructrag
공식 코드InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales
https://github.com/westlake-autolab/biokgbench.github.io
공식 코드BioKGBench: A Knowledge Graph Checking Benchmark of AI Agent for Biomedical Science
https://github.com/wgcyeo/UniversalRAG
공식 코드UniversalRAG: Retrieval-Augmented Generation over Corpora of Diverse Modalities and Granularities
https://github.com/whuhsy/geo-fub
공식 코드https://github.com/williamliujl/Qilin-Med
공식 코드Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model
https://github.com/wlzhang2020/reasonrag
공식 코드Process vs. Outcome Reward: Which is Better for Agentic RAG Reinforcement Learning
https://github.com/wpydcr/mes-rag
공식 코드MES-RAG: Bringing Multi-modal, Entity-Storage, and Secure Enhancements to RAG
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