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Victoria Gil

@mvictoriagil.bsky.social
13 followers 26 following 0 posts

Energy Proceses and Emission Reduction (PrEM) Group at CSIC-INCAR

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Reposted by Victoria Gil
Andres M Bran @andresbran.bsky.social · 12/03/2025
LLMs are pretty bad at writing molecules, but quite good at analyzing mols and reactions! In our new work we use LLMs+search in chemical tasks, unlocking steerable synth. planning and mechanism prediction 🌟 Chehck out the paper 👉 arxiv.org/abs/2503.08537 1/8
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Reposted by Victoria Gil
Chemical Society Reviews @chemsocrev.rsc.org · 06/03/2025
From @kjablonka.com, @mvictoriagil.bsky.social, @pepe-marquez.bsky.social and colleagues. 'From text to insight: large language models for chemical data extraction' #OpenAccess 🔓 pubs.rsc.org/en/content/a...
pubs.rsc.org
From text to insight: large language models for chemical data extraction
The vast majority of chemical knowledge exists in unstructured natural language, yet structured data is crucial for innovative and systematic materials design. Traditionally, the field has relied on m...
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Reposted by Victoria Gil
Pepe Márquez @pepe-marquez.bsky.social · 03/01/2025
Our data extraction tutorial is now online in Chem. Soc. Rev. The notebooks can be run using the #jupyter4nfdi service from #base4nfdi. 📝 Paper: pubs.rsc.org/en/content/a... 💻 JupyterHub: t1p.de/matextract-cpu 📚 Online book: matextract.pub 📽️ intro from @kjablonka.com! 👇
pubs.rsc.org
From text to insight: large language models for chemical data extraction
The vast majority of chemical knowledge exists in unstructured natural language, yet structured data is crucial for innovative and systematic materials design. Traditionally, the field has relied on m...
0236
Reposted by Victoria Gil
Kevin Jablonka @kjablonka.com · 21/12/2024
🎅🏼 A small early Christmas present from our team. To celebrate the publication of our data extraction tutorial in Chem Soc Rev, we made it easy to run it — without any installation — on a JupyterHub of the Base4NFDI. 🎥 Video intro to the JupyterHub deployment: youtu.be/l-5QNUo1fcU
pubs.rsc.org
From text to insight: large language models for chemical data extraction
The vast majority of chemical knowledge exists in unstructured natural language, yet structured data is crucial for innovative and systematic materials design. Traditionally, the field has relied on m...
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