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Ai Paper Digest

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 About Ai Paper Digest

Claude AI가 매일 arXiv 최신 LLM 논문을 읽고, 한국어로 요약합니다.

Platforms

Web Self-hosted

Languages

TypeScript

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Ai Paper Digest

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AI Paper Digest

Daily AI paper & community digest, curated for developers building with AI.

Next.js Claude AI TypeScript License

paper-digest.app · 한국어



What is this?

Every morning, hundreds of AI papers and community posts come out. Most of them aren't useful if you're a developer building products with AI — they're about model training, benchmarks without actionable takeaways, or domain-specific research you'll never apply.

AI Paper Digest cuts through the noise. It automatically collects from arXiv, HuggingFace, Hacker News, and Reddit every day, runs strict AI-powered screening, and delivers summaries designed for developers who use AI agents, prompting, and RAG — not ML researchers.

The bar is high: roughly 1 in 10 papers makes it through.


How it works

A GitHub Actions pipeline runs automatically every day at 07:00 KST:

Step Script Source Filter Output
1. Collect papers collect-papers.ts arXiv 100 + HuggingFace 40 Claude Haiku screening (score ≥ 7) Max 2/day
2. Collect community collect-community.ts HN 100 + Reddit 150 Claude Haiku screening (score ≥ 6) Max 10/day
3. Summarize community digest-community.ts Full post + comments Claude Sonnet Max 10/day
4. Summarize papers summarize.ts Full PDF text Claude Sonnet Max 2/day
5. Translate translate.ts Korean summaries Claude Sonnet Max 12/day
6. Redeploy redeploy.yml Vercel production deploy
7. Slack drip api/cron/slack-drip cron-job.org (every 5min) Max 20/day

Screening criteria for papers — passes only if:

  • Immediately applicable without model training or infra setup
  • A developer can change their prompting or tool usage based on this
  • Non-obvious, not already common knowledge

Screening criteria for community — passes only if:

  • Technical tutorial, deep dive, or real-world experience with AI tools
  • Developer workflow or productivity content with substance

Each summary includes:

  • TL;DR (one-liner)
  • Core mechanics / key findings
  • Evidence with specific numbers
  • How to apply
  • Terminology glossary
  • Korean and English

Slack Integration

Add to your Slack workspace directly from the site. Summaries are delivered throughout the day — no feed to check, no tab to keep open.


Tech Stack

Area Tech
Framework Next.js 15, React 19, TypeScript 5
AI Claude Sonnet (summarization) · Haiku (screening)
Database Turso + Drizzle ORM
Styling Tailwind CSS v4 + shadcn/ui
Infra GitHub Actions + Vercel + cron-job.org

Run locally

git clone https://github.com/kangraemin/ai-paper-digest.git
cd ai-paper-digest
npm install
cp .env.example .env.local
npx drizzle-kit push
npm run dev   # http://localhost:3000

Contributing

PRs welcome. Bug reports and feature requests via Issues.

License

MIT