214 citations · 214 across the 3 of their papers we have counts for
4 papers
Dynamic language model representations for multi-objective reaction optimisation
Joshua W. Sin, David Ming Segura, Bojana Ranković +8
Optimising chemical reactions across multiple objectives, such as yield, selectivity, and safety, is central to chemical synthesis, and model-driven approaches depend critically on…
Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language
David Ming Segura, Jeremy Goumaz, Joshua W. Sin +2
Transformer models have revolutionized natural language processing (NLP), and text-based molecular representations like SMILES have successfully extended these architectures to che…
Large language models as uncertainty-calibrated optimizers for experimental discovery
Bojana Ranković, Ryan-Rhys Griffiths, Philippe Schwaller
Scientific discovery increasingly depends on efficient experimental optimization to navigate vast design spaces under time and resource constraints. Traditional approaches often re…
14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon
Kevin Maik Jablonka, Qianxiang Ai, Alexander Al-Feghali +50
Large-language models (LLMs) such as GPT-4 caught the interest of many scientists. Recent studies suggested that these models could be useful in chemistry and materials science. To…