![[2606.02245] When Knowledge Is Not Free: Cost-Aware Evidence Selection in Retrieval-Augmented Generation](/static/img/curated/desks/afbytes-tech.png)
[2606.02245] When Knowledge Is Not Free: Cost-Aware Evidence Selection in Retrieval-Augmented Generation
Abstract page for arXiv paper 2606.02245: When Knowledge Is Not Free: Cost-Aware Evidence Selection in Retrieval-Augmented Generation
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[2605.31176] Retriever Portfolios: A Principled Approach to Adaptive RAG
Abstract page for arXiv paper 2605.31176: Retriever Portfolios: A Principled Approach to Adaptive RAG
[2605.31010] MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation
Abstract page for arXiv paper 2605.31010: MoG: Mixture of Experts for Graph-based Retrieval-Augmented Generation
[2605.30790] On the impact of retrieved content representations in RAG Pipelines
Abstract page for arXiv paper 2605.30790: On the impact of retrieved content representations in RAG Pipelines
Chaos Engineering Has a Blind Spot. Agentic AI Lives in It.
Chaos tests can prove your RAG pipeline survived failure, but not that it stayed correct. Learn how behavioral checks catch silent AI drift.
[2605.28017] Can It Reach the Generator? Investigating the Survival of Prompt-Injection Attacks in Realistic RAG Settings
Abstract page for arXiv paper 2605.28017: Can It Reach the Generator? Investigating the Survival of Prompt-Injection Attacks in Realistic RAG Settings
[2605.28112] A Wolf in Sheep's Clothing: Targeted Routing Hijacking in Federated RAG
Abstract page for arXiv paper 2605.28112: A Wolf in Sheep's Clothing: Targeted Routing Hijacking in Federated RAG