https://github.com/yzhangchuck/sentinel
공식 코드Sentinel: Decoding Context Utilization via Attention Probing for Efficient LLM Context Compression
Papers with Code 아카이브
Retrieval-augmented Generation
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zaiwen/cropgpt
공식 코드ShizishanGPT: An Agricultural Large Language Model Integrating Tools and Resources
https://github.com/zeroentropy-cc/legalbenchrag
공식 코드LegalBench-RAG: A Benchmark for Retrieval-Augmented Generation in the Legal Domain
https://github.com/zetaalphavector/ragelo
공식 코드Evaluating RAG-Fusion with RAGElo: an Automated Elo-based Framework
https://github.com/zeyang919/librelog
공식 코드LibreLog: Accurate and Efficient Unsupervised Log Parsing Using Open-Source Large Language Models
https://github.com/zhang-yingyi/lsrp
공식 코드LSRP: A Leader-Subordinate Retrieval Framework for Privacy-Preserving Cloud-Device Collaboration
https://github.com/zhentingqi/rag-privacy
공식 코드https://github.com/zhichaoxu-shufe/context-aware-decoding-qfs
공식 코드Context-aware Decoding Reduces Hallucination in Query-focused Summarization
https://github.com/zhiyuanpeng/eloq
공식 코드ELOQ: Resources for Enhancing LLM Detection of Out-of-Scope Questions
https://github.com/zhukun1020/noisefilter_ib
공식 코드https://github.com/zitongyang/synthetic_continued_pretraining
공식 코드https://github.com/zju-daily/aistorian
공식 코드AIstorian lets AI be a historian: A KG-powered multi-agent system for accurate biography generation
https://github.com/zjunlp/omnithink
공식 코드OmniThink: Expanding Knowledge Boundaries in Machine Writing through Thinking
https://github.com/zmzhang2000/trustworthy-alignment
공식 코드Trustworthy Alignment of Retrieval-Augmented Large Language Models via Reinforcement Learning
https://github.com/zoeyyes/confact
공식 코드Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMs
https://github.com/zomss/garag
공식 코드https://github.com/zorazrw/filco
공식 코드Learning to Filter Context for Retrieval-Augmented Generation
https://huggingface.co/aminhaeri/risk-embed
공식 코드Generative AI Enhanced Financial Risk Management Information Retrieval
https://github.com/ArionDas/Generative_AI_Research
Retrieval-Augmented Generation for AI-Generated Content: A Survey
https://github.com/Grecil/Corrective-RAG
https://github.com/InternLM/opencompass
BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack
https://github.com/JingfenQiao/ColPali-Reproducibility
ColPali: Efficient Document Retrieval with Vision Language Models
https://github.com/MS-P3/code6/tree/main/rag
RAG and RAU: A Survey on Retrieval-Augmented Language Model in Natural Language Processing
https://github.com/MindCode-4/code-4/tree/main/qwen2_vl
RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models
https://github.com/MindSpore-scientific-2/code-10/tree/main/MicAugment
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/MindSpore-scientific-2/code-4/tree/main/QuantExplainNLP_AlgoAnalysis
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/MindSpore-scientific-2/code-5/tree/main/MicAugment
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/MindSpore-scientific-2/code-8/tree/main/MicAugment
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/MindSpore-scientific-2/code-8/tree/main/QuantExplainNLP_AlgoAnalysis
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/NVIDIA/Star-Attention
BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack
https://github.com/RUCAIBox/R1-Searcher
ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding
https://github.com/TheAiSingularity/graphrag-local-ollama
From Local to Global: A Graph RAG Approach to Query-Focused Summarization
https://github.com/Wangyuhao06/IKEA
Silent Leaks: Implicit Knowledge Extraction Attack on RAG Systems through Benign Queries
https://github.com/WenqiJiang/SC-ANN-FPGA
RAGO: Systematic Performance Optimization for Retrieval-Augmented Generation Serving
https://github.com/Zefty/rag-end2end-retriever
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
https://github.com/abhijeet3922/vision-RAG
ColPali: Efficient Document Retrieval with Vision Language Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.