Op

OpenPaper – Understand Papers Using AI (Open-Source)

Hacker News

OpenPaper – Understand Papers Using AI (Open-Source)

Hi HN! Open Paper allows you to annotate and understand your research papers with an AI copilot. I wanted a paper-reading assistant that let met actually dig into papers in-place while benefiting from AI tooling. When it comes to studying, I'm not a fan of the typical chat interfaces that obfuscate uploaded files and turn them into black box 'content'. Hence, I've implemented a split-pane view. To mitigate the risk of hallucinations, all AI responses come with grounded citations that refer back to the source material in-flow. Some feature highlights: - Actually read your papers in one place with an AI chat - Generate an audio overview from any paper - Find related papers (powered by OpenAlex) - Every AI response comes with grounded citations - Inline annotations - Compose your knowledge base with uploaded papers - Swap between GPT4 and Gemini2.5 Pro - Shareable annotations What are you looking for in a research assistant? Would love to get some thoughts / feedback on what I've built so far :). Thank you! Check out the GitHub --> https://github.com/sabaimran/openpaper

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Product HuntOn track for Day 1 leaderboard · Strong signals: gemini, using, open · Missing: mac, agents, macos
83%83% 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 NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
49%49% 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 · Missing: mobile apps, ios, personal
49%49% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting
32%32% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive
30%30% 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
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat, audio · Missing: web3, crypto, cryptocurrency
1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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