Optimizing document retrieval using massive text embeddings and LLM prompt engineering.

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Title: Optimizing document retrieval using massive text embeddings and LLM prompt engineering.
Authors: Mitrov G; Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Rugjer Boshkovik 16, Skopje, 1000, North Macedonia.; Magix.AI, Cyril and Methodius 3A, Skopje, 1000, North Macedonia., Stanoev B; Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Rugjer Boshkovik 16, Skopje, 1000, North Macedonia.; Magix.AI, Cyril and Methodius 3A, Skopje, 1000, North Macedonia., Trajkovik V; Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Rugjer Boshkovik 16, Skopje, 1000, North Macedonia., Risteska Stojkoska B; Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Rugjer Boshkovik 16, Skopje, 1000, North Macedonia., Basnarkov L; Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Rugjer Boshkovik 16, Skopje, 1000, North Macedonia., Lameski P; Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Rugjer Boshkovik 16, Skopje, 1000, North Macedonia., Kampel M; Computer Vision Lab, TU Wien, Favoritenstr. 9/193-1, Vienna, 1040, Austria. martin.kampel@tuwien.ac.at., Zdravevski E; Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Rugjer Boshkovik 16, Skopje, 1000, North Macedonia.; Magix.AI, Cyril and Methodius 3A, Skopje, 1000, North Macedonia.
Source: Systematic reviews [Syst Rev] 2026 Apr 14; Vol. 15 (1). Date of Electronic Publication: 2026 Apr 14.
Publication Type: Journal Article
Journal Info: Publisher: BioMed Central Country of Publication: England NLM ID: 101580575 Publication Model: Electronic Cited Medium: Internet ISSN: 2046-4053 (Electronic) Linking ISSN: 20464053 NLM ISO Abbreviation: Syst Rev Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2046-4053
DOI:10.1186/s13643-026-03155-4