Show HN: I built a tool that explains ArXiv papers in simple language(arxivexplained.com)
arxivexplained.com
Show HN: I built a tool that explains ArXiv papers in simple language
https://arxivexplained.com
2 comments
How long do you need to wait after uploading a new arXiv paper to be reviewed by your app for the AI summaries and audio to be available? Is there any kind of notification for the end user when the new AI summary is available? Also, where would I look for the AI summaries of the newly uploaded paper as there is no search facility by paper title in your app?
The ai content should be created within an hour but sometimes it takes up to 24 hours. I'm thinking about adding a notification system. Im looking right now and all papers have content generated so whatever paper you added should be ready.
No search feature yet but the home page shows latest research in the order it was published so you can find the latest hot papers that way.
No search feature yet but the home page shows latest research in the order it was published so you can find the latest hot papers that way.
What it does: It's a free app with audio explanations of the latest AI research papers. Each paper gets a ~5 minute breakdown in simple language - no jargon, just clear explanations of what the researchers did and why it matters. Key feature: The app already comes loaded with all the popular and recent AI papers, so you can browse and discover the latest research right away. You don't need to bring your own papers - just open the app and start exploring what's new in AI.
How I use it: I pop in my earbuds during my commute or while doing chores and listen to explanations of cutting-edge research. It's like having someone explain the latest breakthroughs to you in plain English.
You can also paste any arXiv link to get a custom explanation, but most people just browse the curated collection of recent papers that's already there. Technical note: It uses AI to analyze papers and generate natural-sounding audio explanations focused on clarity over complexity.
Would love to hear your feedback, especially if you try it with papers from your field!