At #EMNLP2026 in Budapest? Come see our poster at the Web-as-Corpus workshop (WaC-13) on 29 Oct. Counting documents is not counting text. 📄 arxiv.org/abs/2608.16390 @commoncrawl.bsky.social #WebData #Crawl
Luca
In Berlin, at the @OSSYM2026 conference, and meeting the full Common Crawl Foundation engineering team! So glad to be here!
We are pleased to announce that pdfalto, the PDF → ALTO XML converter behind GROBID, is now on PyPI 🎉 pip install pdfalto Binary bundled in the wheels, no manual setup, plus a Python API. pypi.org/project/pdf... github.com/kermitt2/...
Python client release note: github.com/grobidOrg... And.. Grobid 0.9.1 release note (in case you missed it) github.com/grobidOrg... 🖖 2/2
🔗 Reworked author–affiliation linking mechanism, up to +8% F1 score; and more: rootless Docker (k8s/OpenShift-ready), DeLFT 0.4.6, various fixes 👉 github.com/kermitt2/... 2/3
Wanna join the community? - Announcement mailing list: grobid.netlify.app/mail - Discord: grobid.netlify.app/d... ... and don't forget to star us on Github #GROBID #NLP #TextMining #PDF #OpenScience #TDM #MachineLearning 3/3
Great experience at #LREC2026! With colleagues and friends from DFKI And Common Crawl, we presented our paper on the SciLaD 🥗 corpus and models arxiv.org/abs/2512.1... 1/4
- Paper: arxiv.org/abs/2512.1... - Models: huggingface.co/colle... - Dataset: huggingface.co/colle... (including English cleaned text only, TEI-XML, JSON, Markdown) 4/4
Great experience at #LREC2026! With colleagues and friends from DFKI And Common Crawl, we presented our paper on the SciLaD 🥗 corpus and models arxiv.org/abs/2512.1... 1/4
4/ 🎨 And finally — we're refreshing the GROBID logo, and you get to pick. Vote here → forms.gle/aGDNma9Qzn... 4/5
5/ ⭐ One last thing: if you find GROBID useful, please star us on GitHub — it goes a long way in helping the project grow. → github.com/grobidOrg... Come help shape what's next. 🙌 5/5
2/ 📬 We've launched an official mailing list (EN/FR) for announcements, discussions, and Q&A. Subscribe → groupes.renater.fr/s... 2/5
3/ 💬 Prefer real-time chat? Join our new Discord server to hang out with users, contributors, and maintainers. Invite → discord.gg/yuEaC4tYnz 3/5
🧵 Excited to share that I'll be presenting SciLaD at #LREC2026! SciLaD: A Large-Scale, Transparent, Reproducible Dataset for Natural Scientific Language Processing arXiv → arxiv.org/abs/2512.1... 1/5
This builds on the foundational harvesting work by Patrice Lopez & James Howison (SoftCite project), and is a collaboration with @DFKI, @HUBerlin, @CommonCrawl & Uni Mannheim. Attending LREC? Let's connect!👋 #NLP #ScientificNLP #MultilingualNLP #SciLaD #ScienciaLAB #grobid 5/5
🧵 Excited to share that I'll be presenting SciLaD at #LREC2026! SciLaD: A Large-Scale, Transparent, Reproducible Dataset for Natural Scientific Language Processing arXiv → arxiv.org/abs/2512.1... 1/5
5/ Infrastructure: JDK 21, Gradle 9, TensorFlow 2.17 (Python 3.10–3.11), pdfalto 0.6.0, wapiti 1.5.1, virtualenv/conda support for DeLFT. 6/ Full release notes → github.com/kermitt2/... #GROBID #OpenSource #NLP #ScholarlyInfrastructure 6/6
If you've ever lost time reformatting citations by hand, this one's for you. sciencialab.github.i... 7/7
We built a simple tool to fix exactly this: text2bibtex. The app is simple: paste any plain-text citation and get a clean, ready-to-use BibTeX entry back. github.com/user-atta... 2/7
Luca reposted
@thomvaughan.bsky.social did a WCAG colour contrast audit of 240 top domains using Common Crawl's February 2026 archive. You can read more about his study in the thread below
What can we measure about accessibility on the web using web archives? TL;DR Large-scale accessibility research can be conducted reproducibly from open crawl archives alone, and colours on the web are mostly quite ugly. thunderpoot.github.io/wcag-audit/ commoncrawl.org/blog/measuri...
Luca reposted
We're happy to announce the release of the Web Graphs for December 2025 and January/February 2026, consisting of 288.6 million nodes and 12.4 billion edges at the host level, and 134.2 million nodes and 5.4 billion edges at the domain level. www.commoncrawl.org/blog/host--a...
Exactly! There is a common misconception that by throwing any kind of crap into a vector it will magically work. Still at the age of AI, metadata information cannot still be ignored.
Vector search is good, but it's not enough. Metadata adds a layer of logic on top of your text chunks. This lets you filter by date or source first, then retrieve all the related pieces at once. #RAG #AI #VectorSearch
Luca reposted
Yes. The time is now. Vaccines to treat and prevent cancer. www.jci.org/articles/vie...