1 citations · 2 across the 7 of their papers we have counts for
5 papers · 1 filter
Mechanistic Reaction Prediction via Discrete Flow Matching on Graph-Structured Electron Occupation
Nguyen Xuan-Vu, Octavian Susanu, Daniel Armstrong +1
Chemical reactions are fundamentally transformations in electron space, yet most machine learning approaches model them either through de novo generation of product molecules or th…
Agentic generation of verifiable rules for deterministic, self-expanding reaction classification
Daniel Armstrong, Maarten Dobbelaere, Valentas Olikauskas +4
Computer-assisted synthesis planning breaks target molecules into accessible precursors using large libraries of reaction rules that assign each transformation a deterministic, int…
Synthelite: Chemist-aligned and feasibility-aware synthesis planning with LLMs
Nguyen Xuan-Vu, Daniel Armstrong, Milena Wehrbach +3
Computer-aided synthesis planning (CASP) has long been envisioned as a complementary tool for synthetic chemists. However, existing frameworks often lack mechanisms to allow intera…
SynthStrategy: Extracting and Formalizing Latent Strategic Insights from LLMs in Organic Chemistry
Daniel Armstrong, Zlatko Jončev, Andres M Bran +1
Modern computer-assisted synthesis planning (CASP) systems show promises at generating chemically valid reaction steps but struggle to incorporate strategic considerations such as…
Chemical reasoning in LLMs unlocks strategy-aware synthesis planning and reaction mechanism elucidation
Andres M Bran, Theo A Neukomm, Daniel P Armstrong +2
While automated chemical tools excel at specific tasks, they have struggled to capture the strategic thinking that characterizes expert chemical reasoning. Here we demonstrate that…