Paper Collector crawls trending papers from HuggingFace every day, then uses an LLM to generate summaries, categories, and tags — so you never miss an important advance in AI.
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Fetches trending papers from the HuggingFace Papers page every day — no manual refreshing or subscriptions needed, so nothing important slips through.
An LLM analyzes each paper's title and abstract in depth and produces a concise, readable summary so you can quickly judge whether a paper is worth a deeper read.
The model identifies each paper's subfield (NLP, CV, RL, and so on) and generates multi-dimensional tags so you can filter by research direction.
Papers are organized by date with full history. This builds a continuous timeline of AI research so you can trace how a field is evolving.
Full-text search across titles, abstracts, and tags. Locate the papers or research directions you care about in seconds.
No sign-up. Open your browser and go. Every feature is free — we want to lower the barrier to scholarly discovery.
Different roles, same productivity win
Spend five minutes a day skimming the day's trending summaries and catch the latest breakthroughs across subfields — no need to open arXiv pages one by one, which saves a lot of time on literature review.
Track papers on model optimization and training tricks relevant to your work. Use tags to surface actionable ideas quickly and stay sharp.
A useful aid for topic selection and proposal work — see which directions are hot. Translated summaries lower the barrier to English papers and accelerate literature review writing.
Stay on top of AI trends without getting lost in the details. Gives you information support for team technology choices and roadmap decisions.
Free, no sign-up, refreshed daily. Open Paper Collector — it's your AI research daily.
Visit Paper CollectorUpload a PDF; the model extracts key information and generates a mind map for paper deep reads and fast technical-document skims.
17 AI agents work together across HR, finance, IT operations, and more — natural-language-driven office workflows.
A transparent proxy for LLM API calls that compresses redundant context. One-line integration cuts spend by 30–60%.
A tiered knowledge database built for AI agents — L0/L1/L2 summaries, MCP integration, and session memory.
Import Bilibili videos or upload local files. AI transcription + contextual Q&A + auto notes makes video learning more efficient.