Research / ICCCI 2026 / Published
MeReader: An Offline, Privacy-Preserving, Progress-Aware AI Assistant for Narrative eBook Reading
Mohammed Efaz, Udo Bub, Itilekha Podder
Springer Communications in Computer and Information Science, volume 3044, pages 321–335. First online 18 September 2026.
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About the research
MeReader runs on consumer hardware and uses only the part of a book the reader has reached. It combines vector search with BM25 keyword search and summaries to retrieve relevant passages. In tests on classic English novels, we compared comprehension and response times across local models, using quantitative measures and model-based assessments. The results suggest that models with 2B to 4B parameters can offer comprehension comparable to larger models within this evaluation. The paper also examines whether the progress boundary keeps future content out of retrieved context and generated answers.
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Cite this paper
Efaz, M., Bub, U., Podder, I. (2027). MeReader: An Offline, Privacy-Preserving, Progress-Aware AI Assistant for Narrative eBook Reading. In: Advances in Computational Collective Intelligence. ICCCI 2026. Communications in Computer and Information Science, vol. 3044, pp. 321–335. Springer, Cham. https://doi.org/10.1007/978-3-032-37936-8_22
Springer uses 2027 for the volume's citation year. The chapter first appeared online on 18 September 2026.
BibTeX
@inproceedings{efaz2027mereader,
author = {Efaz, Mohammed and Bub, Udo and Podder, Itilekha},
title = {MeReader: An Offline, Privacy-Preserving, Progress-Aware AI Assistant for Narrative eBook Reading},
booktitle = {Advances in Computational Collective Intelligence},
series = {Communications in Computer and Information Science},
volume = {3044},
pages = {321--335},
year = {2027},
publisher = {Springer Nature Switzerland},
doi = {10.1007/978-3-032-37936-8_22},
url = {https://doi.org/10.1007/978-3-032-37936-8_22}
}