31 citations · 110 across the 10 of their papers we have counts for
4 papers · 1 filter
From Text to Insight: Large Language Models for Materials Science Data Extraction
Mara Schilling-Wilhelmi, Martiño Ríos-García, Sherjeel Shabih +5
The vast majority of materials science knowledge exists in unstructured natural language, yet structured data is crucial for innovative and systematic materials design. Traditional…
Less can be more for predicting properties with large language models
Nawaf Alampara, Santiago Miret, Kevin Maik Jablonka
Predicting properties from coordinate-category data -- sets of vectors paired with categorical information -- is fundamental to computational science. In materials science, this ch…
Are large language models superhuman chemists?
Adrian Mirza, Nawaf Alampara, Sreekanth Kunchapu +32
Large language models (LLMs) have gained widespread interest due to their ability to process human language and perform tasks on which they have not been explicitly trained. Howeve…
Are LLMs Ready for Real-World Materials Discovery?
Santiago Miret, N M Anoop Krishnan
Large Language Models (LLMs) create exciting possibilities for powerful language processing tools to accelerate research in materials science. While LLMs have great potential to ac…