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Explain Like I'm Five for ArXiv Papers

Hacker News

Explain Like I'm Five for ArXiv Papers

"ELI: Explain Like I'm..." makes academic research more accessible to the general population. That includes kids, teens, and curious adults! Drop in an arXiv paper url at https://eli.voxos.ai or use the chrome extension ( https://chromewebstore.google.com/detail/eli-explain-like-im... ) to quickly open a paper up in ELI. Not all research material is age-appropriate! ELI handles this by providing parents with an MPAA rating selector to put safeguards up as they see fit. It offers a several bells and whistles: 1. Export to multiple formats: PDF, Print, Markdown, BibTeX, RIS 2. Drop in bookmarks for those longer papers 3. Curate your personal reading lists and share them with others 4. Share with friends and family Want to know more about ELI? Visit https://eli.voxos.ai/what-is-eli Do you have any ideas on how to improve ELI as a tool to promote STEM education and improve public sentiment around science and research? I'd love to hear from you!

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Product HuntOn track for Day 1 leaderboard · Strong signals: google, open, plain · Missing: mac, agents, macos
78%78% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
63%63% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
48%48% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: personal, google, education · Missing: mobile apps, ios, entrepreneurs
43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
41%41% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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