DifyのRAGで検索スコアを回答許可に使わない:根拠を検査する品質ゲート

RECAST is a learned framework that builds evidence through sequential retrieval and computation steps instead of standard RAG's fixed similarity lookup. It treats evidence construction as a decision process, useful for tasks where answers must…
"Build a voice agent for IoT alarms with Amazon Nova 2 Sonic" by Godwin Vincent
New on Foojay by Luqman Saeed: Learn how to add RAG (Retrieval-Augmented Generation) to your Jakarta EE 11 application using just the JDK and Jakarta specifications. No extra dependencies needed.
RAG or Fine-Tuning?
📚 RAG → Current & private business knowledge
🎯 Fine-Tuning → Specialized AI behavior
🚀 Both → Knowledge + customization
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A new RAG approach for EDA documentation groups related artifacts into functional units and trains an encoder to align queries with them, combining unit and chunk retrieval to handle scattered, tightly coupled technical…
#RAG #EDADocs #DocQA #InformationRetrieval
https://arxiv.org/abs/2610.09361
#AISearch #RAG #GoogleAI https://netcontentseo.com/article/google-releases-a-740m-multimodal-retrieval-model-private-ai-search-and-rag-can-now-run-entirely-on-device-1267 (2/2)
Three production checks worth keeping:
Is an agent needed?
Does the citation support the claim?
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Autonomous AI Lakehouseのデータを Ontologyでつないで Private Agent Factoryから NL2SQL+RAG+Knowledge Graphしてみてみた
RAG systems need to honor source permissions, not just retrieve text. Amazon Quick and Bedrock Knowledge Bases now verify document-level…
#RAG #AWS #EnterpriseAI #AccessControl
https://aws.amazon.com/blogs/machine-learning/rethinking-access-control-for-rag-with-amazon-quick-and-amazon-bedrock/
Amazon QuickとAmazon BedrockによるRAGのアクセス制御の再設計
Amazon QuickとAmazon Bedrockを活用したRAGシステムにおける、セキュアなアクセス制御の革新的なアプローチを解説。
TriCalRAG is a reproducible benchmark for on-premise log-anomaly detection and root-cause analysis, evaluating Qwen2.5-14B and Mistral-Small-22B on vLLM with one NVIDIA RTX PRO 6000 GPU across BGL, HDFS, Thunderbird, and OpenStack. It…
#TriCalRAG #AIOps #RAG #vLLM
https://arxiv.org/abs/2609.14762
MDKeyChunker asks whether one LLM call per chunk for metadata beats Markdown's free structure in RAG retrieval, testing it with qwen2.5:7b across BM25, dense, and hybrid setups on Qasper and FreshStack datasets. The…
#RAG #Markdown #LLM #InformationRetrieval
https://arxiv.org/abs/2603.23533
MCP Tool Server Context7 Agent: Stop stuffing 100k tokens into system prompts. Context7 streams surgical RAG chunks via FastMCP, cutting token costs by 76% and dropping hallucinations to 1.1%. Full blueprint: https://botskillstack.com/bots/mcp-tool-server-context7-agent #RAG #
La respuesta reproduce bien el documento. El documento rige otro caso.
Recuperación, fidelidad y aplicabilidad son comprobaciones distintas al evaluar un RAG. Una cita abre la revisión; no la termina.
"Evaluating retrieval-augmented generation versus long-context input for clinical reasoning over electronic health records" RAG used <8K tokens; imaging improved; diagnosis stable. #RAG #EHR buff.ly/1DMfj7P
"What I Learned on My AWS Al Practitioner Journey" by Vaibhava Kumar Shrivastav
#artificial-intelligence #amazon-bedrock #aws-certification #generative-ai #rag