Generative modeling with proteins (hundreds of them either):

EquiJump: Protein Dynamics Simulation via SO(3)-Equivariant Stochastic Interpolants
Design of Ligand-Binding Proteins with Atomic Flow Matching
RapidDock: Unlocking Proteome-scale Molecular Docking
Deep Learning for Protein-Ligand Docking: Are We There Yet?
ProteinBench: A Holistic Evaluation of Protein Foundation Models
Fast and Accurate Blind Flexible Docking
Solving Inverse Problems in Protein Space Using Diffusion-Based Priors

Crystals and Materials:

Flow Matching for Accelerated Simulation of Atomic Transport in Materials
MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks
Learning the Hamiltonian of Disordered Materials with Equivariant Graph Networks
Designing Mechanical Meta-Materials by Learning Equivariant Flows
SymmCD: Symmetry-Preserving Crystal Generation with Diffusion Models
Rethinking the role of frames for SE(3)-invariant crystal structure modeling
A Periodic Bayesian Flow for Material Generation
ECD: A Machine Learning Benchmark for Predicting Enhanced-Precision Electronic Charge Density in Crystalline Inorganic Materials
Wyckoff Transformer: Generation of Symmetric Crystals
PDDFormer: Pairwise Distance Distribution Graph Transformer for Crystal Material Property Prediction