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RAGについて情報をまとめる（後半）

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LLM
RAG
idea

以下の前半の続き
https://zenn.dev/karaage0703/articles/50a3830046f5fc

RAGの性能改善のテクニック

RAG関係の論文

RAG関係のサーベイ論文
https://arxiv.org/abs/2312.10997


画像はRetrieval-Augmented Generation for Large Language Models: A Surveyより引用

時系列のまとめ
https://note.com/rrrrrrrrrr_666/n/nb8c9010ce603

まとめのGitHubリポジトリ
https://github.com/Tongji-KGLLM/RAG-Survey

サーベイ論文の解説記事 RAG（検索拡張生成）包括的な論文をわかりやすく解説

コサイン類似度が本当に適しているのかをといかける論文
https://arxiv.org/abs/2403.05440

retrieval-augmented thoughts(RAT)という手法について書かれた論文
https://arxiv.org/abs/2403.05313

RAGのエラーの分類に関する論文
https://arxiv.org/abs/2403.01193

HyDEという手法の論文
https://arxiv.org/abs/2212.10496

HyDEのノートブック

メタ認知をRAGに適用
https://arxiv.org/abs/2402.11626

Self RAG
https://arxiv.org/abs/2310.11511

Self RAGノートブック

https://zenn.dev/yamada_quantum/articles/ab41b431581eba

NVIDIA Order-Preserve RAG
https://arxiv.org/abs/2409.01666

RAGのスケーリング則
https://arxiv.org/abs/2410.04343

https://arxiv.org/abs/2412.21023

グラフ（GraphRAG）

https://www.creationline.com/tech-blog/68014

https://qiita.com/Ruuchami/items/294d797798d4fca346ad

https://arxiv.org/abs/2306.08302

https://arxiv.org/abs/2402.05391

https://arxiv.org/abs/2408.04913

https://pnch.hatenablog.com/entry/graphrag

https://www.alpha.co.jp/blog/202408_01/

https://zenn.dev/knowledgesense/articles/077ad1ab0f9ff6

https://techblog.insightedge.jp/entry/knowledgegraph-recommendation

https://qiita.com/ssfujita/items/65a952f299190f4c1e6a

https://zenn.dev/kun432/scraps/1f28e5d20dfdf5

https://github.com/gusye1234/nano-graphrag

https://github.com/HKUDS/LightRAG

https://zenn.dev/sashimimochi/articles/197b3e7e7caf66

https://caddi.tech/2025/04/02/110800

実践

https://note.com/npaka/n/n6d33c2181050

https://note.com/npaka/n/n63afe0e6684a

https://zenn.dev/cloud_ace/articles/19bd3554ac8432

https://zenn.dev/spiralai/articles/8af7cbf526c2e1

https://tech-blog.abeja.asia/entry/in-house-jargon-slackbot-with-rag-202402

https://zenn.dev/smartshopping/articles/rag-with-bedrock-and-openai

https://qiita.com/ksonoda/items/ba6d7b913fc744db3d79

https://qiita.com/mitsumizo/items/469d79c5e81d9189a9e4

https://speakerdeck.com/soracom/history-of-soracom-support-bot-20240321

https://qiita.com/minorun365/items/24dfb0ea3afde6ed0a56

https://qiita.com/moritalous/items/76ba9f2ad200df335d07

https://zenn.dev/yumefuku/articles/llm-langchain-rag

https://qiita.com/Naoki_Ishihara/items/662d70a9bd0dc3a8c9ce?1

https://zenn.dev/aidemy/articles/97d5fb6ac03a4f

https://zenn.dev/umi_mori/books/prompt-engineer/viewer/pdf_langchain_chatgpt

https://qiita.com/hiroki_okuhata_int/items/7102bab7d96eb2574e7d

https://zenn.dev/aidemy/articles/cd79fe964ebbff

https://blog.g-gen.co.jp/entry/comparing-rag-architecture-across-cloud-vendors

https://acro-engineer.hatenablog.com/entry/2024/08/22/120000

https://speakerdeck.com/takapy/di-kosutodeshi-xian-surushe-nei-wen-shu-ragji-neng-woda-zai-sitaaitiyatutobotutokai-fa

https://speakerdeck.com/forrep/rag-does-not-need-a-vector-db

https://blog.studysapuri.jp/entry/2024/06/26/100000

https://note.com/kan_hatakeyama/n/nd851fd842515

https://techblog.exawizards.com/entry/2024/11/01/151609

https://tech-blog.abeja.asia/entry/advent-2024-day24

https://speakerdeck.com/hotchpotch/ask-nikkei-ragjian-suo-ji-shu-noshen-ceng

RAGの評価

RAGの評価ソフト
https://github.com/explodinggradients/ragas

https://www.nogawanogawa.com/entry/ragas

RAGの評価に関するサーベイ論文
https://arxiv.org/abs/2405.07437

https://zenn.dev/knowledgesense/articles/bfd100c51ff34e

https://www.nogawanogawa.com/entry/rag_eval

https://github.com/IntelLabs/RAGFoundry

https://techblog.lycorp.co.jp/ja/20240819a

https://tech.assured.jp/entry/2024/08/20/130000

https://zenn.dev/knowledgesense/articles/90ac35eedf8b7c

https://www.nogawanogawa.com/entry/rag_eval_2

https://arxiv.org/abs/2408.08067

ブログ記事

https://note.com/npaka/n/n53e8aabed0f2

https://note.com/npaka/n/n62cd25213679

https://logmi.jp/tech/articles/329143

LLMのRAGを用いたコンペ
https://zenn.dev/nishimoto/articles/aff1fba9c75c34

https://docs.llamaindex.ai/en/stable/examples/index_structs/doc_summary/DocSummary/

https://speakerdeck.com/payanotty/embeddingmoderuwoshi-tutabekutoruhua-nosikumi-fine-tuningshou-fa-wojie-shuo

https://blog.soracom.com/ja-jp/2024/07/12/soracom-support-bot/

https://zenn.dev/google_cloud_jp/articles/598d52341cc56f

https://zenn.dev/kun432/scraps/c0642e79169635

https://qiita.com/ksonoda/items/f3c703fb7b689fd65868

https://zenn.dev/minedia/articles/d9f01aa05bc880

https://uepon.hatenadiary.com/entry/2025/01/19/231410

https://uepon.hatenadiary.com/entry/2025/01/21/232926

https://speakerdeck.com/shukob/lun-wen-shao-jie-long-context-llms-meet-rag-overcoming-challenges-for-long-inputs-in-rag-at-gdg-tokyo

まとめ

たくさんありすぎですね。

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