1 citations · 1 across the 2 of their papers we have counts for
4 papers
Molecular Representations for Large Language Models
Nicholas T. Runcie, Fergus Imrie, Charlotte M. Deane
Large Language Models (LLMs) are increasingly being used to support scientific discovery. In chemistry, tasks such as reaction prediction and structure elucidation require reasonin…
SigmaDock: Untwisting Molecular Docking With Fragment-Based SE(3) Diffusion
Alvaro Prat, Leo Zhang, Charlotte M. Deane +2
Determining the binding pose of a ligand to a protein, known as molecular docking, is a fundamental task in drug discovery. Generative approaches promise faster, improved, and more…
Assessing the Chemical Intelligence of Large Language Models
Nicholas T. Runcie, Charlotte M. Deane, Fergus Imrie
Large Language Models are versatile, general-purpose tools with a wide range of applications. Recently, the advent of "reasoning models" has led to substantial improvements in thei…
An evaluation of unconditional 3D molecular generation methods
Martin Buttenschoen, Yael Ziv, Garrett M. Morris +1
Unconditional molecular generation is a stepping stone for conditional molecular generation, which is important in \emph{de novo} drug design. Recent unconditional 3D molecular gen…