Post #1499814
2026-04-15 15:22 UTC
@malteengeler
It's probably still the same underlying LLM logic, but working on a very constrained corpus (compared to Google summaries) and providing links back to the full sources. In this sense, it's more like a catalogue search, that gives you a sense of the content of a groups of documents, rather than just list of individual documents organized by "author, title, date, keyword".
If you care, you still have to read the paper, but you can access it differently and perhaps find relevant papers more quickly across a larger search space, and we are all dealing with way larger search spaces than before, even, and particularly, in academia.
Replies (1)
-
@malteengeler@legal.social 2026-04-15 15:35
@festal I personally don't feel encouraged by the promise of "random statistical nonsense but based on a more narrow set of data". I still consider it a problem that the model used as the base has all the integrated homogenisation - and applies it to the data set. The abstract is created from a limited set of text but the model used was trained on much bigger sets (I just checked but can't find what model they used. They didn't train one themselves on only sci-hub texts I assume).