Confidential Retrieval-Augmented Generation in Educational Contexts

This work presents a confidentiality-aware Retrieval-Augmented Generation (RAG) framework designed for educational applications.
The proposed approach ensures privacy-preserving document retrieval and generation, validated through experiments on BEIR/FiQA datasets.

Recommended citation: Boratto L., Congiu F., Fenu G., Medda G. (2025). Confidential Retrieval-Augmented Generation in Educational Contexts. In Proceedings of WAILS 2025.