physics.chem-phOct 7, 2026

Looking Under the Streetlight: Evaluation in Generative Molecular Dynamics

Authors: Simon Olsson, Frank Noé, Grant M. Rotskoff, Kresten Lindorff-Larsen

Organizations: Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg SE-41296 Gothenburg, Sweden · Microsoft Research Berlin · Stanford University · University of Copenhagen

Abstract

This position paper argues that the generative molecular dynamics (GenMD) community is not properly evaluating its progress: current evaluations let a model match what is reported while being arbitrarily wrong on what was claimed, which risks over-claiming advantage over classical baselines. This reflects a structural misalignment between common evaluation practices and the scientific tasks the field sets for itself. The reason is that the ground truth---exhaustive molecular dynamics on the systems of interest---is computationally costly, and this cost is what motivates the field. With ground truth inaccessible, evaluation drifts toward convenient proxies, and the resulting norms entrench easily. We identify misaligned evaluation patterns that persist as a community-level equilibrium, and propose concrete observables, reporting standards, and benchmark designs, both computational and experimental, that better reflect what GenMD aspires to deliver. Our aim is to give the field shared language and tools for evaluation that match its scientific ambitions before today's conventions calcify into norms.

Figures & tables

Explore similar work

CardsList
  1. AquaGen: Scaling generative models to molecular dynamics precision on thousands of atoms

    Jul 3, 2026Emmanuel Bengio, Sanjeev Raja, Yui Tik Pang +5Free Energy CalculationBoltzmann Sampling

  2. MDGYM: Benchmarking AI Agents on Molecular Simulations

    May 9, 2026Vinay Kumar, Satyendra Rajput, Mausam +1AI Agents for Scientific DiscoveryAI Agent Evaluation

  3. HEDGEHOG: Hierarchical Evaluation of Drug Generators Through Rigorous Filtration

    Jul 14, 2026Daria A. Ryabchenko, Pavel Gurevich, Shamil Kadyrov +5Molecular GenerationGenerative AI Evaluation