2 papers
cs.IR2026
On the Representational Limits of Quantum-Inspired 1024-D Document Embeddings: An Experimental Evaluation Framework
Dario Maio
Text embeddings are central to modern information retrieval and Retrieval-Augmented Generation (RAG). While dense models derived from Large Language Models (LLMs) dominate current…
cs.IR2026
Bridging OLAP and RAG: A Multidimensional Approach to the Design of Corpus Partitioning
Dario Maio, Stefano Rizzi
Retrieval-Augmented Generation (RAG) systems are increasingly deployed on large-scale document collections, often comprising millions of documents and tens of millions of text chun…