Budget-Constrained Online Retrieval-Augmented Generation: The Chunk-as-a-Service Model
Large Language Models (LLMs) have revolutionized the field of natural language processing. However, they exhibit some limitations, including a lack of reliability and transparency: they may hallucinate and fail to provide sources that support the generated output. Retrieval-Augmented Generation (RAG) was introduced to address such limitations in LLMs. One popular implementation, RAG-as-a-Service (RaaS), has shortcomings that hinder its adoption and accessibility. For instance, RaaS pricing is based on the number of submitted prompts, without considering whether the prompts are enriched by relevant chunks, i.e., text segments retrieved from a vector database, or the quality of the utilized...
| Authors | Shawqi Al-Maliki, Ammar Gharaibeh, Mohamed Rahouti et al. |
|---|---|
| Primary category | cs.IR |
| Published | 28 April 2026 |
| Last updated at source | 28 April 2026 |
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