MolRGen: A Training and Evaluation Setting for De Novo Molecular Generation with Reasonning Models

ArXi:2603.18256v1 Announce Type: cross Recent advances in reasoning-based large language models (LLMs) have nstrated substantial improvements in complex problem-solving tasks. Motivated by these advances, several works have explored the application of reasoning LLMs to drug discovery and molecular design. However, most existing approaches either focus on evaluation or rely on