Possibly. I had to kind of be very specific to get the model to link to the pages in a specific format my frontend can parse and then interact with the pdf viewer[1]. It seems very full featured so it may have a way to highlight portions of the page, but my experience with PDFs leads me to believe it would be tricky.
That seems like a social network? This is just a tool to have an AI model answer questions without needing to do anything other than replace the domain.
I've had better results running it with the Gemini 2.5 Pro model but it's much more expensive. The website is using the very cheap 2.5 flash lite model.
You can run it yourself using the better model to see if you get better results as well:
Very cool! I chose gemini for two reasons; the first being it supported pdf input and the second the flash lite model being very cheap so I could comfortably make it public and free.
Thank you, that's probably correct. I think the gemini api might turn the pages into images and use those. Sending the original tex source was something I thought of but not all papers have those submitted.
As for markdown / latex output that could be done, especially for equations! I'll have to look into the best way to render that.
Shameless plug but I made a similar tool called asXiv[1] which allows you to "ask" arXiv.org papers questions.
It also recommends questions on initial load that can help understand or explore the paper, here's a demo[2] from the popular Attention Is All You Need paper.
The code is all opensource[3], it uses the google 2.5 flash lite model to keep costs down (it's completely free atm), but that can be changed via env var if you run it locally.
Right. I do this all the time with Gemini. Add a pdf or a link and ask it whatever I want. It will even turn it into a podcast with two people discussing the entire paper that I can listen to on the tram to work.
whoa this is fantastic. wish I had known about this earlier! just made a similar product for reading arXiv / epub / pdfs called Ruminate (www.tryruminate.com), would love to hear what you think
https://asxiv.org/pdf/1706.03762