This is really cool, and very relevant to something I'm working on. Would you be willing to do a quick explanation of the build?
0101111101•2h ago
Sure! I first used openai embeddings on all the paper titles, abstracts and authors. When a user submits a search query, I embed the query, find the closest matching papers and return those results. Nothing too fancy involved!
I just did a spot check, I think searchthearxiv search results are superior.
0101111101•1h ago
Looks cool!
You can input either a search query or a paper URL on arxiv xplorer. You can even combine paper URLs to search for combinations of ideas by putting + or - before the URL, like `+ 2501.12948 + 1712.01815`
masterjack•1h ago
There’s also the search and browsing on https://sugaku.net, it’s more focused on math but does also have all of the arxiv on it
nblgbg•33m ago
Just curious, are there any techniques other than using embeddings, computing cosine similarity, and sorting the results based on that? RRF could be used but again its very simple as well.
elliotec•3h ago
0101111101•2h ago
I'm also maintaining a dataset of all the embeddings on kaggle if you want to use them yourself: https://www.kaggle.com/datasets/tomtum/openai-arxiv-embeddin...