I love this and wanted to build this - but https://www.alphaxiv.org/ already exists, and it gets no social action (hardly any papers have comments), so this makes me doubtful about this.
I am interested to hear if anyone knows why the format may not resonate with researchers or those reading papers in general?
My own reason is that to get value from a "social" site the number of interactions has to be high and of a fast speed for people to continue to engage, which is maybe not possible to hit on research papers.
People will not flock somewhere unless they sense some potential return on investment. If a website looks like it will disappear in a few months, it does not make sense for a user to invest time and effort into it.
You have to either invest a lot to get a critical mass to join your site, or make it extremely entertaining to be there from the start. Apart from all the criticism, this is what Facebook, Instagram, Twitter, and LinkedIn got right from the start. For their intended audiences, it is either useful or fun to be on their platforms.
I don't see much added value for most arXiv extensions, except for SemanticScholar [1], which might have been lucky being one of the first.
I could see the author using GenAI video creation to summarize and make short videos about each paper. I believe this format could do wonders for paper discovery - say choose "Computer science" and you could flip through 20 papers in a few minutes getting an idea of what research recently has been published.
Other formats are dense and require reading and internalizing the content
Just wanted to maybe make a light suggestions that, for marketing purposes, this really doesn't need any suggestion of TikTok and also might benefit from less heavy handed mentions of AI. I think it provides a real value proposition on its own without needing to rely on those two things to sell itself. They are pretty polarized terms at this point and I can sort of understand the initial revulsion from hearing TikTok next to scientific papers.
I appreciate those things are mentioned front and centre, because it reveals the mindset and goals of the author, which is a useful signal. Depending on the person that signal either means “give it to me now” or “I’m going to stay far far away from this”, but either way it’s useful to know.
There are plenty of reasons to not use Twitter which are unrelated to AI. And there certainly are people on Mastodon who are so into LLMs, it’s all they post about.
I think there is something to it. It seems that "TikTok" part is actually minimal, but it is bound, from purely marketing perspective, to drive some people here away. You might as well say something along the lines of Uber for bananas or "we pivot banana to AI and we are now Nutella AI"
I'm unsure that the tiktok model works because it's designed around fast, easy to consume content, whereas scientific papers require sitting down and really digesting the material. It's much easier to read dense text on a desktop/tablet over mobile. The times where I read arxiv on mobile, it's really just the abstract. If you summarize each abstract into concise bullet points that might be quite useful.
What I don't understand about these specialized social networks, that obviously won't exist in a few months as they won't get traction, is why not just use the existing social networks?
Instead of some LinkedIn / TikTok / Facebook / Insta for X, create a group or channel in an existing network. Create a subreddit, or Facebook group or telegram channel. There are a number of existing social networks that are good at creating sub-communities. I don't want to join another social media platform.
Because many people, especially here, hate for various reasons the established social networks?
They are ad financed, clickbait driven "engangement" machines, that are designed to make people addictive and do not respect their users at all.
So TikTok for scientific papers already makes me not want to engage with the concept. But a social network with a focus on science is something I am interested. But the base would need to be solid. Where I can trust that they do not sell out to some ad network in 2 months after they established some users.
Because you don’t control the existing social network, meaning you can’t exploit and profit from the users in a group¹, which is the whole point of making a digital social networks².
¹ And if you do find a way, the parent network will simply eat you up.
I think the AI portion is not just something that ought have a toggle, but it should not be part of the platform.
Somewhat recently, the ACM (one of the premier publishers for computer science) integrated AI-generated summaries for all papers, and it made these summaries appear in place of author-written abstracts; to find the abstract, users had to use a toggle. The ACM argued that this was a benefit. After significant community pushback, the ACM has swapped things: author-written abstracts now appear first, but users are still offered a toggle to access AI-generated summaries instead.
As highlighted by professor Anil Madhavapeddy [1], the AI summaries are often factually incorrect, sometimes obviously, but often subtly. This sentiment was corroborated by numerous colleagues of mine less publicly: they checked the AI-generated summaries of their own papers, and for almost every paper were able to identify at least one factually incorrect or significantly misleading statement.
Some people argue that AI-generated summaries help to democratize academia; I think instead they are democratizing misunderstanding. The models fundamentally lack the capacity to "understand" when what they say is wrong or misleading. It is not uncommon that I have students in office hours with severe misgivings about our course material because they asked an LLM some innocuous question to which they thought surely the LLM would generate an accurate response. The course material is, of course, drawn from various sources, so the LLM ought be fairly likely to generate accurate responses. In contrast, a publication is often (or, by definition in my field, necessarily) introducing novel conclusions; this means that the LLM is less likely to generate an accurate summary for a paper than for course materials, and the course material summaries are already problematic enough, so I think applying this to research is just a bad move.
I understand the appeal. I understand how liberating it must feel to someone to get to "talk to" a paper to seek greater understanding. But if you already don't know enough about the material that this is useful, you also don't know enough to know when the responses are subtly incorrect, and I think this completely undermines the purpose of publication in the first place.
What make TikTok, well TikTok, is the frictionless experience.
When I opened the link, I expected to directly be shown the target content. If there's a login screen or any explanation to do, it should either be postponed or integrated into the experience.
In some ways I like the concept. Making interesting papers easier to find and easier to digest seems like a good thing.
But the popularity metrics and AI aspects seem like they will cause a bias towards certain types of papers, making potentially useful ones not get found.
I've enjoyed consuming information about interested research papers on instagram, and insta has been good at showing me more of such content. But I think a dedicated platform would be great too! It takes such scientific content creators lots of time to create a script, hook, include animations or other visual aids and also put the research in perspective with it's potential implications in the long terms. I am not sure if AI would be able to do a good job (yet).
My $0.02 try creating an AI powered science channel on YT or insta before spending time on creating a dedicated app.
careful there, you are saying blasphemerous things around these lands, that an algorithmic feed of content you dont follow can be more useful than a reverse chronological feed
Good idea. Right now I started with iOS because I wanted to experiment with the reading/saving flow and on-device features, but an accountless web preview would probably make sense, especially for HN.
Seems like a cool idea, but also really niche. I could see a map tool as part of this video thingy where you can see word/phrase associations between adjacent papers as a similarity and connection search?
I like the idea. As others suggested it might be a good idea to drop the branding. Had the same considerations when I built a “Tinder” (1) for RSS Feeds. In the end it worked fine, if not better.
I think you’re right. The “TikTok” phrasing was useful shorthand for the interaction model and as provocation, but it also sends the wrong signal about the goal.
FYI I'm getting "Too many signups right now. Please try again in a few minutes." when trying to sign up to the waiting list. (congrats haha, but good to fix)
I hope it’s not purely ai generated, but who knows, maybe it is and it’s still interesting and informative. It could still be with such huge volume and high signal basis. Wish I’d thought of this actually.
Just what humanity needed: TikTok for scientific papers, with AI! I find myself looking up to the sky wishing for an asteroid to hit Earth on a daily basis, lately...
Is your negativity a knee-jerk reaction to TikTok and AI, or do you have a substantive criticism of the idea?
There are so many papers being written these days that it's difficult to find all the ones that are relevant to your work and interests. Likewise, there's a discoverability problem for authors who are not already well-known. Andrej Karpathy's arXiv Sanity site used to be a decent way of sifting through papers in some areas, but sadly it's been down for a while now.
I did the same thing as parent, but from the other end. I liked the start, but then I started going negative as I realized that the medium of 'presenting a lot structured information' and the medium of 'lets make it appealing to a visual person' do not have a lot of overlap. There is some, but there is a valid question of whether "TikTok, but for papers" is not just a bad way to advertise it to people reading papers, people on HN, but ALSO to people who consume TikTok.. it prepares a mediocre experience for all 3 groups.
It is an interesting mix though. I am not dismissing it outright. After all, I am driving ford lightning and kinda like ratty..
I am interested to hear if anyone knows why the format may not resonate with researchers or those reading papers in general?
My own reason is that to get value from a "social" site the number of interactions has to be high and of a fast speed for people to continue to engage, which is maybe not possible to hit on research papers.
You have to either invest a lot to get a critical mass to join your site, or make it extremely entertaining to be there from the start. Apart from all the criticism, this is what Facebook, Instagram, Twitter, and LinkedIn got right from the start. For their intended audiences, it is either useful or fun to be on their platforms.
I don't see much added value for most arXiv extensions, except for SemanticScholar [1], which might have been lucky being one of the first.
[1] https://www.semanticscholar.org/
Other formats are dense and require reading and internalizing the content
Instead of some LinkedIn / TikTok / Facebook / Insta for X, create a group or channel in an existing network. Create a subreddit, or Facebook group or telegram channel. There are a number of existing social networks that are good at creating sub-communities. I don't want to join another social media platform.
They are ad financed, clickbait driven "engangement" machines, that are designed to make people addictive and do not respect their users at all.
So TikTok for scientific papers already makes me not want to engage with the concept. But a social network with a focus on science is something I am interested. But the base would need to be solid. Where I can trust that they do not sell out to some ad network in 2 months after they established some users.
Because you don’t control the existing social network, meaning you can’t exploit and profit from the users in a group¹, which is the whole point of making a digital social networks².
¹ And if you do find a way, the parent network will simply eat you up.
² Outside of a few truly ideological non-profits.
So the question stays the same: why is this not just a Mastodon server?
Somewhat recently, the ACM (one of the premier publishers for computer science) integrated AI-generated summaries for all papers, and it made these summaries appear in place of author-written abstracts; to find the abstract, users had to use a toggle. The ACM argued that this was a benefit. After significant community pushback, the ACM has swapped things: author-written abstracts now appear first, but users are still offered a toggle to access AI-generated summaries instead.
As highlighted by professor Anil Madhavapeddy [1], the AI summaries are often factually incorrect, sometimes obviously, but often subtly. This sentiment was corroborated by numerous colleagues of mine less publicly: they checked the AI-generated summaries of their own papers, and for almost every paper were able to identify at least one factually incorrect or significantly misleading statement.
Some people argue that AI-generated summaries help to democratize academia; I think instead they are democratizing misunderstanding. The models fundamentally lack the capacity to "understand" when what they say is wrong or misleading. It is not uncommon that I have students in office hours with severe misgivings about our course material because they asked an LLM some innocuous question to which they thought surely the LLM would generate an accurate response. The course material is, of course, drawn from various sources, so the LLM ought be fairly likely to generate accurate responses. In contrast, a publication is often (or, by definition in my field, necessarily) introducing novel conclusions; this means that the LLM is less likely to generate an accurate summary for a paper than for course materials, and the course material summaries are already problematic enough, so I think applying this to research is just a bad move.
I understand the appeal. I understand how liberating it must feel to someone to get to "talk to" a paper to seek greater understanding. But if you already don't know enough about the material that this is useful, you also don't know enough to know when the responses are subtly incorrect, and I think this completely undermines the purpose of publication in the first place.
[1] https://anil.recoil.org/notes/acm-ai-recs
OP should come back once there's an actual product, assuming it ever gets past the email harvesting stage.
When I opened the link, I expected to directly be shown the target content. If there's a login screen or any explanation to do, it should either be postponed or integrated into the experience.
But the popularity metrics and AI aspects seem like they will cause a bias towards certain types of papers, making potentially useful ones not get found.
My $0.02 try creating an AI powered science channel on YT or insta before spending time on creating a dedicated app.
Is the gravity set very high or am I getting too old to play Flappy Bird with Transformers?
This looks amazing. I hope Android will be an option.
Seems like a cool idea, but also really niche. I could see a map tool as part of this video thingy where you can see word/phrase associations between adjacent papers as a similarity and connection search?
(1) https://philippdubach.com/posts/rss-swipr-find-blogs-like-yo...
FYI I'm getting "Too many signups right now. Please try again in a few minutes." when trying to sign up to the waiting list. (congrats haha, but good to fix)
I joined the waiting list.
I hope it’s not purely ai generated, but who knows, maybe it is and it’s still interesting and informative. It could still be with such huge volume and high signal basis. Wish I’d thought of this actually.
There are so many papers being written these days that it's difficult to find all the ones that are relevant to your work and interests. Likewise, there's a discoverability problem for authors who are not already well-known. Andrej Karpathy's arXiv Sanity site used to be a decent way of sifting through papers in some areas, but sadly it's been down for a while now.
It is an interesting mix though. I am not dismissing it outright. After all, I am driving ford lightning and kinda like ratty..