SinAE: A Single-Architecture Flow-Matching Autoencoder for Cross-Domain Atomic Systems

Jul 15, 2026

SinAE is a flow-matching autoencoder that uses a single vanilla Transformer architecture to handle molecules, crystals, and proteins, without relying on domain-specific operators. It achieves near-lossless reconstruction across these domains and demonstrates strong generative performance, with joint training on molecules and crystals leading to improvements in both domains.

Why it matters: This work provides a unified approach for generative modeling across diverse atomic systems, enabling cross-domain transfer and potentially alleviating data scarcity issues.

Full story at: arXiv Machine Learning ↗