ADT：面向 3D 分子结构的全原子扩散分词器
ADT: All-Atom Diffusion Tokenizer for 3D Molecular Structures
一篇新论文：ADT 用扩散模型来给 3D 分子结构做 token 化，小分子按原子、蛋白按残基编码，重建时还能补回侧链细节，做分子生成方向的朋友可以看看。
ADT（All-atom Diffusion Tokenizer）提出将 token 粒度与重建分辨率解耦：小分子每个原子对应一个 token，蛋白质每个残基一个 token，同时编码主链和侧链几何信息。为缓解量化带来的几何失真，方法引入扩散模型来恢复确定性解码无法还原的细粒度原子几何。实验覆盖小分子和蛋白质两类对象，ADT 在紧凑离散表示下实现较强重建，并支持高质量的自回归 3D 分子生成。
ADT: All-Atom Diffusion Tokenizer for 3D Molecular Structures
Discrete structural tokenization provides a promising route to autoregressive 3D molecular generation. Yet, existing tokenizers face a trade-off between compact representation and all-atom reconstruction: atom-level tokens preserve atomic details but produce long sequences, while compact residue-level protein tokens typically omit side-chain geometry. To overcome this limitation, we propose All-atom Diffusion Tokenizer (ADT), which decouples token granularity from reconstruction resolution. ADT uses one structural token per atom for small molecules and one token per protein residue that jointly represents backbone and side-chain geometry. To mitigate geometric distortion introduced by quantization, we leverage the generative capacity of diffusion models to recover fine-grained atomic geometry beyond deterministic decoding from discrete tokens. Extensive experiments across small molecules and proteins demonstrate that ADT achieves strong reconstruction from compact discrete representations while enabling high-quality autoregressive generation of both small molecules and all-atom protein structures. These results establish compact structural tokens as an effective discrete interface for all-atom molecular reconstruction and generation.
