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Papers.Data.Code

Daily signal from the ML noise.

We automatically track, score, and publish the best papers, repositories, and datasets from the ML world — every day.

Selected, not collected.

What we do

Our pipeline scans arXiv, GitHub, Hugging Face, and Kaggle daily, scores each item, and publishes the top picks. No hype, no noise. Just signal.

What we cover

Type Sources
Papers arXiv
Repos GitHub
Datasets Hugging Face, Kaggle

Where to follow

Why it's different

PDC combines automated scoring with quality filters and ranks each work across weekly, monthly, quarterly, and yearly horizons — so you see what actually holds momentum, not just what's new.

How rankings work

Each work is ranked by an internal score across multiple horizons. Top picks at one level pull into the next: weekly winners pool into monthly, monthly into quarterly, quarterly into yearly.

Structure of this repo

  • digests/[year]/weekly/ — weekly Top 3 (papers, repos, datasets) and recap with TL;DR and Trends
  • digests/[year]/monthly/ — monthly rankings, recap, and tracking metrics for top picks
  • digests/[year]/quarterly/ — quarterly rankings and recap
  • digests/[year]/yearly/ — year-end rankings and recap
  • digests/ru/[year]/... — Russian digests in the same structure

Each period has paired files: main digest with top 3 by category and a recap with TL;DR and Trends.

File naming: date-first for chronological sorting (e.g. 2026-05-10-W19.md).

License

MIT for metadata. Original papers and code retain their respective licenses.

Contact

📧 papers.data.code@gmail.com

About

ML research tracker. Top papers, repos & datasets from arXiv, GitHub, Hugging Face & Kaggle. Weekly, monthly, quarterly, yearly digests. Selected, not collected.

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