2 citations · 3 across the 4 of their papers we have counts for
5 papers
MiST: Understanding the Role of Mid-Stage Scientific Training in Developing Chemical Reasoning Models
Andres M Bran, Tong Xie, Shai Pranesh +9
Large Language Models can develop reasoning capabilities through online fine-tuning with rule-based rewards. However, recent studies reveal a critical constraint: reinforcement lea…
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…
Position: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI
Sha Zhang, Suorong Yang, Tong Xie +18
Scientific discovery has long been constrained by human limitations in expertise, physical capability, and sleep cycles. The recent rise of AI scientists and automated laboratories…
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…