3 papers
cs.LG2026
URSA: Chemistry-Aware Benchmark for Utilitarian Retrosynthesis Assessment
Bogdan Zagribelnyy, Ivan Ilin, Nikita Bondarev +7
Synthesis planning aiming to find pathways of reactions for a target molecule is one of the most important and challenging tasks in drug discovery. Recent progress has produced bot…
cs.LG2026
When Single Answer Is Not Enough: Rethinking Single-Step Retrosynthesis Benchmarks for LLMs
Bogdan Zagribelnyy, Ivan Ilin, Maksim Kuznetsov +10
Recent progress has expanded the use of large language models (LLMs) in drug discovery, including synthesis planning. However, objective evaluation of retrosynthesis performance re…
cs.LG2026
MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery
Maksim Kuznetsov, Zulfat Miftahutdinov, Rim Shayakhmetov +17
General-purpose large language models (LLMs) that rely on in-context learning do not reliably deliver the scientific understanding and performance required for drug discovery tasks…