Sm

SmartXiv: AI-Powered ArXiv Digest with Personalized Recommendations

Hacker News

SmartXiv: AI-Powered ArXiv Digest with Personalized Recommendations

As a researcher, I created SmartXiv to solve a problem I faced every day: keeping up with the overwhelming number of research papers uploaded to arXiv. With over 1000 new papers each day, finding the most relevant research was time-consuming and exhausting. I needed a smarter way to stay updated. What SmartXiv Does • Personalized Recommendations: Using advanced AI, SmartXiv analyzes your interests and sends you daily emails with research papers that align with your preferences. •Efficient Research: By curating the latest papers for you, SmartXiv saves you hours of research. • Fully Customizable: You can tailor your updates by categories, subcategories, and frequency to match your specific needs. How It Works •Setup: Select your preferred arXiv sections and customize your notification settings. •Daily Updates: Receive a curated list of relevant papers, complete with summaries and key information. •AI Analysis: SmartXiv’s AI analyzes your interactions and improve its recommendations. Your feedback is more than welcome as we continue to improve and refine the service. Contact email: giannisinsights@gmail.com

Share card

Actual performance

6points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: new, email, using · Missing: mac, agents, macos
64%64% 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 · Strong signals: created · Missing: supports, reddit linkedin, podcasting
62%62% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, way · Missing: mobile apps, ios, entrepreneurs
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: 000, io · Missing: https docs, excited, just released
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
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 · Strong signals: smart · 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

Similar products

Pe
Peloton Personalized Recommendations37%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Peloton Personalized Recommendations

Hacker News5
Genoutfit
Genoutfit29%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI-Powered Personalized Outfit Recommendations

Indie Hackers1ai
I
I made an LLM-powered HN digest personalized just for you36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

I made an LLM-powered HN digest personalized just for you

Hacker News3
TasteLanc
TasteLanc47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

An app providing personalized dining and nightlife recommendations in Lancaster, PA.

TrustMRR15$750/moArtificial Intelligence
symphonAI
symphonAI61%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI powered music recommendations

Indie Hackers1ai
Pe
Personalized book recommendations with Librarian AI41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Personalized book recommendations with Librarian AI

Hacker News150
Arbeitr
Arbeitr17%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Personalized job recommendations that go beyond the paycheck

Indie Hackers2ai
Lorekeep
Lorekeep42%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Personalized book recommendations

Product Hunt+1
AI-Powered Supplement Quiz
AI-Powered Supplement Quiz34%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Personalized supplement recommendations with lead capture

Indie Hackerscommitment-side-project
Ol
Ollie – AI powered gift recommendations35%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Ollie – AI powered gift recommendations

Hacker News9