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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/gair-nlp/deepresearcher

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DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments

https://github.com/gair-nlp/openresearcher

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OpenResearcher: Unleashing AI for Accelerated Scientific Research

https://github.com/gasolsun36/dynamicrag

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DynamicRAG: Leveraging Outputs of Large Language Model as Feedback for Dynamic Reranking in Retrieval-Augmented Generation

https://github.com/gasolsun36/surf

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SURf: Teaching Large Vision-Language Models to Selectively Utilize Retrieved Information

https://github.com/gautierdag/plancraft

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Plancraft: an evaluation dataset for planning with LLM agents

https://github.com/gblackout/lm-os

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The Compressor-Retriever Architecture for Language Model OS

https://github.com/georgiarg/autofashion

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Automatic Generation of Fashion Images using Prompting in Generative Machine Learning Models

https://github.com/getzep/graphiti

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Zep: A Temporal Knowledge Graph Architecture for Agent Memory

https://github.com/ggendro/causal-cartographer

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Causal Cartographer: From Mapping to Reasoning Over Counterfactual Worlds

https://github.com/gjq100/graph-counselor

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Graph Counselor: Adaptive Graph Exploration via Multi-Agent Synergy to Enhance LLM Reasoning

https://github.com/gk0wk/xgraphrag

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XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation

https://github.com/gomate-community/trustrag

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TrustRAG: An Information Assistant with Retrieval Augmented Generation

https://github.com/gomes-lab/AiSciVision

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AiSciVision: A Framework for Specializing Large Multimodal Models in Scientific Image Classification

https://github.com/google-research-datasets/rag_conflicts

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DRAGged into Conflicts: Detecting and Addressing Conflicting Sources in Search-Augmented LLMs

https://github.com/google-research/google-research/tree/master/table_rag

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TableRAG: Million-Token Table Understanding with Language Models

https://github.com/govtech-responsibleai/knowornot

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Know Or Not: a library for evaluating out-of-knowledge base robustness

https://github.com/gowitheflow-1998/rar-b

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RAR-b: Reasoning as Retrieval Benchmark

https://github.com/gpt-laboratory/rag-llm-development-guidebook-from-pdfs

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Developing Retrieval Augmented Generation (RAG) based LLM Systems from PDFs: An Experience Report

https://github.com/graph-com/subgraphrag

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Simple Is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation

https://github.com/graphrag-bench/graphrag-benchmark

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When to use Graphs in RAG: A Comprehensive Analysis for Graph Retrieval-Augmented Generation

https://github.com/h-tayyarmadabushi/a-frame-semantics-based-approach-for-improved-factual-accuracy-in-large-language-models

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FS-RAG: A Frame Semantics Based Approach for Improved Factual Accuracy in Large Language Models

https://github.com/halueval-wild/halueval-wild

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HaluEval-Wild: Evaluating Hallucinations of Language Models in the Wild

https://github.com/hannibal046/selfmemory

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Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory

https://github.com/hannight/ramdocs

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Retrieval-Augmented Generation with Conflicting Evidence

https://github.com/haodongze/self-ksel-qans

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Self-Bootstrapped Visual-Language Model for Knowledge Selection and Question Answering

https://github.com/haruhi-sudo/FTHSS

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Streamlining the Collaborative Chain of Models into A Single Forward Pass in Generation-Based Tasks

https://github.com/haruhi-sudo/RPG

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Retrieve-Plan-Generation: An Iterative Planning and Answering Framework for Knowledge-Intensive LLM Generation

https://github.com/hessaalawwad/plr-tqa

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Enhancing textual textbook question answering with large language models and retrieval augmented generation

https://github.com/heydaari/CAG

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Context Awareness Gate For Retrieval Augmented Generation

https://github.com/heydarsoudani/ragvsft

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Fine Tuning vs. Retrieval Augmented Generation for Less Popular Knowledge

https://github.com/hhhuang/cag

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Don't Do RAG: When Cache-Augmented Generation is All You Need for Knowledge Tasks

https://github.com/hhy-huang/HiRAG

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Retrieval-Augmented Generation with Hierarchical Knowledge

https://github.com/hitsz-tmg/cognitive-visual-language-mapper

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A Comprehensive Evaluation of GPT-4V on Knowledge-Intensive Visual Question Answering

https://github.com/hkuds/autoagent

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AutoAgent: A Fully-Automated and Zero-Code Framework for LLM Agents

https://github.com/hkuds/lightrag

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LightRAG: Simple and Fast Retrieval-Augmented Generation

https://github.com/hkuds/minirag

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MiniRAG: Towards Extremely Simple Retrieval-Augmented Generation

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