matt1

I think you might be getting the two projects mixed up.

Emergent Mind, my tool, has been in the works for over two years. If that's the interface you're referring to, thank you.

Asxiv, what this post is about, was built in a day by the OP.

Impressive project, especially for a day's work!

My site, https://www.emergentmind.com, is similar, though I'm two years in :)

I've found Gemini 2.5 Flash is the best model in terms of speed/cost/quality. Pro is great as well, but probably not necessary for most chat-with-paper functionality.

I'll add too that building an AI layer on top of arXiv is a deep, deep rabbit hole depending on how far you want to take the project. Drop me a note if you want to chat more about my experience with it.

Regardless, thanks for sharing this!

My site, https://www.emergentmind.com, is exactly for this. It surfaces trending AI/ML/CS papers, summarizes them, links to social commentary, lets you read and download papers, links to topics, and more. Would love any feedback you have!

Hey all, I’m Matt Mazur, the founder of Emergent Mind, a new AI research assistant that helps you learn about any computer science research topic.

You can ask it questions (“What’s the difference between DPO and PPO?”), look up topics (“Graph Convolutional Neural Networks”), learn about papers (“KAN: Kolmogorov-Arnold Networks”), and research authors (“Yann LeCun”). Behind the scenes, it will try to find the most relevant computer science papers on arXiv, then synthesize their findings to generate a detailed, research-backed answer for you, all in a matter of seconds.

Unlike tools like ChatGPT, Emergent Mind is hyper-focused on computer science. It factors in citations and social media metrics to help rank papers (including Hacker News upvotes). It provides references so you know what papers the answers came from, is always up-to-date with arXiv (about 670k comp sci papers and counting), and encourages exploration using automatically-generated follow-up questions and topic links (similar to Wikipedia).

The tool is still fairly new and there’s endless room for improvement, but we wanted to share it with you all to get any feedback to make sure our product roadmap is aligned with what folks would find most useful.

Hey all, Matt here, Emergent Mind's founder.

Yes, Emergent Mind is 100% focused on AI/ML papers from arXiv. I think it makes more sense to focus on a niche because you can tailor everything to that niche, vs creating a general research paper site which won't wind up speaking to any audience well.

For anyone curious about Emergent Mind: it surfaces trending AI/ML papers by monitoring social media (HackerNews, Reddit, X, YouTube, and GitHub) for discussions about papers, then ranks them based on the amount of engagement they're getting (similar to how HackerNews uses upvotes). Then, for all trending papers, it automatically summarizes them using GPT-4o and links to relevant discussions so you can learn more.

We're working on a bunch of new capabilities that we'll announce soon too.

Feedback welcome: [email protected]

If you're a fan of tldr-ai, you might also like my site, EmergentMind.com, which does something similar: it surfaces trending AI papers based on social media engagement (including HackerNews upvotes!), then summarizes those papers using GPT-4 (a bullet point summary + detailed writeup based on the actual content of the paper), and highlights discussions on HN, Reddit, YouTube, GitHub, and X about that paper.

I don't want to highjack this launch post (we definitely need more tools in this space!), just wanted to share my tool for anyone interested since it's related. Feedback welcome: [email protected].

It does feed each paper through GPT-4 to generate an overview of it, including the main conclusions. Here's a demo I shared on X which walks through it: https://twitter.com/mhmazur/status/1747990900771287097

X has an API that costs $100/month: https://help.twitter.com/en/rules-and-policies/x-api

You can use it to fetch tweets with links to arxiv papers, but be watchful of their 10k tweet-read requests/month limit.

Which ad blockers are you using? I'll take a look to figure out what's up.

Hey all - I'd like to invite you all to check out Emergent Mind, a website I built to make it easier to stay informed about important new AI/ML research.

It works by monitoring HN, X, Reddit, YouTube, and GitHub for mentions of new arXiv AI/ML papers, and then surfacing trending papers for you. It also runs each paper through GPT-4 to generate an overview (including defining all technical terms) and links to those social media discussions and other resources (GitHub, YouTube videos, references, and related papers) so you can learn more. A lot of the UI and features are inspired by my experience browsing HN for many years.

I shared a 4-minute demo video on X for anyone interested in learning more: https://twitter.com/mhmazur/status/1747990900771287097

Questions/feedback welcome!

Hey, thanks for the kind words.

To answer your question: an earlier version of the site focused on surfacing AI news, but that space is super competitive and I don't think Emergent Mind did a better job than the other resources out there. I tried selling it instead of just shutting it down, but ultimately decided to keep it. I recently decided to pivot to covering arXiv papers, which is a much better fit than AI news. I think there's an opportunity with it to not only help surface trending papers, but help educate people about them too using AI (the GPT-4 summaries are just a start). A lot of the future work will be focused in that direction, but I'd also love any feedback folks have on what I could add to make it more useful.

OP here with a shameless plug: for anyone interested, I'm working on a site called Emergent Mind that surfaces trending AI/ML papers. This TinyLlama paper/repo is trending #1 right now and likely will be for a while due to how much attention it's getting across social media: https://www.emergentmind.com/papers/2401.02385. Emergent Mind also looks for and links to relevant discussions/resources on Reddit, X, HackerNews, GitHub, and YouTube for every new arXiv AI/ML paper. Feedback welcome!

FYI I started embedding the HTML pages in an iframe on Emergent Mind when the HTML version is available: https://www.emergentmind.com/papers/2312.11444 // should make it even easier to stay informed about trending papers

I'm slowly adding older papers as I work out the kinks in the site. Down the road when the database is more comprehensive, this should definitely be possible.

Great site, thanks for sharing. Can you explain how you're determining how many times a paper is cited? Obviously papers include a list of references, but extracting them accurately from the PDF is difficult in my experience (two column formats, ugh) - though the new HTML versions help. And even if you have a list, many authors just mention arXiv paper titles, not their ids, making identifying specific references tricky.

Just a note to say that factoring authors into the ranking system is high on my todo list. v1 won't be too fancy - just a hardcoded list of prominent authors whose papers warrant extra visibility. A future version will likely automate it to avoid the hardcoded list.

Also, soon-ish I'm going to add the ability for users to follow specific authors, so you can get notified when they publish new papers.

Thanks! If you ever run into any issues or have any suggestions for improving the site, drop me a note: [email protected].

Can you (or anyone experiencing similar issues) share any details about what's not working in Firefox? I tested it and all is well for me, though it's definitely possible there's an issue with some other version of it.

Thanks for the kind words, it's appreciated.

I might add comments down the road if there's enough interest and if there's enough traffic to warrant it. Don't want to add them just yet and have zero comments on everything and it look like a ghost town.

Keep the suggestions coming though as you use it more: [email protected].

Thanks! I've got a lot more planned for it too. If anyone has any feedback that doesn't make sense to share here, or if you're a researcher who is open to some questions about how you currently follow arXiv papers, drop me a note at [email protected].