Scholarly-Search

TL;DR for operators A specialised research platform does not need to discard its documents, metadata, search history, licensing rules, or expert workflows to add an AI assistant. ReSearch_SSH1 instead proposes a modular layer over the existing ISIDORE infrastructure. The design combines multilingual domain adaptation with retrieval that connects documents through authors, institutions, themes, citations, and other relationships rather than returning isolated text matches. Most retrieval, reranking, generation, and public knowledge components could be reused elsewhere. ...

Search used to be a polite negotiation with a database. You typed keywords. The system returned papers. You inspected titles, opened tabs, skimmed abstracts, cursed quietly, adjusted the keywords, and repeated the ritual until either the literature became clear or your soul left the building. Large language models changed the ritual, but not always for the better. Now a system can answer a research question directly, which feels magical until one remembers that “fluent” and “correct” are not synonyms. In scholarly work, this distinction is not academic decoration. It is the difference between literature discovery and very confident misinformation wearing a lab coat. ...