alt.hn

5/20/2025 at 9:49:36 PM

Semantic search engine for ArXiv, biorxiv and medrxiv

 https://arxivxplorer.com/

by 0101111101

5/21/2025 at 9:52:22 AM

Using "+" and "-" in search is interesting idea.

I've built similar thing for github stars[1], might implement the same for it.

[1]: https://starscout.xyz/

by itzlambda

5/21/2025 at 12:28:54 AM

embedding search via https://searchthearxiv.com/ takes either a word vector, or an abs or pdf link to an arxiv paper.

https://news.ycombinator.com/item?id=42519487

I just did a spot check, I think searchthearxiv search results are superior.

by sitkack

5/21/2025 at 12:54:52 AM

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`

by 0101111101

5/21/2025 at 11:55:51 AM

That is neat I like that.

It would be cool if the "More Like This" had a + button that would append the arxiv id to the search query.

by sitkack

5/21/2025 at 2:22:11 PM

That's a nice idea! Might take a look this weekend!

by 0101111101

5/21/2025 at 1:23:01 AM

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

by masterjack

5/21/2025 at 2:15:45 AM

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.

by nblgbg

5/21/2025 at 8:02:58 AM

My understanding is that your levers are roughly better / more diverse embeddings or computing more embeddings (embed chunks / groups / etc) + aggregating more cosine similarities / scores. More flops = better search w/ steep diminishing returns

Colbert being a good google-able application of utilizing more embeddings.

Search ends up often being a funnel of techniques. Cheap and high recall for phase 1 and ratchet up the flops and precision in subsequent passes on the previous result set.

by forrestp

5/21/2025 at 2:25:02 PM

Exactly! A near property of the matryoshka embeddings is that you can compute a low dimension embedding similarity really fast and then refine afterwards.

by 0101111101

5/20/2025 at 11:10:41 PM

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?

by elliotec

5/21/2025 at 12:25:26 AM

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'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...

by 0101111101

5/21/2025 at 3:19:30 AM

So did you just combine Title+Abstracts+Authors into a single chunk and embed them or embedded them individually?

by heisenburgzero

5/21/2025 at 5:17:33 AM

Impressive! Will you parse the papers in the future? Without citations this is not that usable for professors or scientists in general. The relevance ranking largely depends on showing these older, prominent papers. (from our lab experience building decentralised search using transformers)

by synctext

5/21/2025 at 2:25:32 PM

One chunk embedded together

by 0101111101

5/21/2025 at 8:46:05 AM

That method can break when author names and subject matter collide.

by cluckindan

5/21/2025 at 2:27:06 PM

True, but similarly if your embeddings are any good they'll capture interesting associations between authors, topics and your search query. If you find any interesting author overlap results I'd be very interested!

by 0101111101

5/21/2025 at 6:52:27 AM

Thank you!!

by elliotec

5/20/2025 at 11:31:43 PM

Looks great! Could you add eprint.iacr.org (Cryptology ePrint Archive)?

by madars

5/21/2025 at 12:25:51 AM

Do they have a public API/dataset?

by 0101111101

5/21/2025 at 12:23:07 AM

Oh god, there's a medrxiv?? TIL...

Don't forget chemrXiv!

by bbor

5/21/2025 at 7:08:48 AM

medrxiv was very useful for keeping the various COVID-19 related preprints from completely swamping biorxiv, especially once biorxiv started aggressively rejecting them.

by Fomite

5/21/2025 at 12:08:26 AM

[dead]

by faffdsf

5/20/2025 at 11:27:44 PM

[flagged]

by fdadsfdsd