A Locally Deployed Multimodal Literature Model System for Lithium Battery Research

Counts differ because each database indexes a different set of publications. We treat OpenAlex as the canonical count; Google Scholar is not shown (no API, and crawling it violates its ToS).

The analysis of scientific literature is usually constrained by the fact that textual conclusions are separated from the figures and tables which support them.Generalpurpose cloud models also rely on external computing services, which may increase latency, cost, and data privacy risks.The present study introduces a locally deployed multimodal literature model system and links textual results with their original graphical evidence while keeping the references to the source papers.The system can operate on existing consumer-grade hardware without additional cloud computing quotas or dedicated high-performance infrastructure.When tested using literature on lithium batteries, the system is found to reduce response latency while improving evidence localization, the quality of the answers remaining comparable to that of general-purpose models.The system is therefore offered as a practical solution for verifiable literature analysis in local research settings where data privacy is a concern.