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HackerNews but for research papers

Hacker News

HackerNews but for research papers

Hey guys, I love HN! I wanted to extend the same aesthetic and community towards things beyond tech-related news. I thought it would be cool to get the same quality of community gathered around the latest and greatest research coming out. Let me know what you guys think of what I have so far. It's still early so there are probably bugs and other quality issues. If there's any features missing that you'd want let me know. ALSO, if any of you are familiar with the map of the territory of any particular field, please let me know! Would love to pick your brain and to come up with a 'most important papers' section for each field. Thank you!! -stefan

Visit product View on Hacker NewsMay 23, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: new · Missing: mac, agents, macos

72%72% 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.

Hacker NewsStrong engagement from HN community · Strong signals: io · Missing: https docs, excited, just released

58%58% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

36%36% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Indie HackersIH features products with proven revenue · Missing: supports, reddit linkedin, podcasting

33%33% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal

30%30% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% 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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