Autoregressive latent diffusion for 3D molecule generation
Three-dimensional (3D) molecule generation has been dominated by diffusion models, which achieve strong generation quality but typically require molecular size to be specified (or predicted) separately before generation. This can be limiting for fragment-based molecule generation, central to drug discovery, where the size of the generated structure is itself part of the design problem. Autoregressive models determine size during generation and naturally support partial-structure conditioning, but balancing unconditional and fragment-conditioned generation remains challenging. We introduce KRONOS, a latent autoregressive diffusion framework that generates molecules in the latent space of a...
| Authors | Federico Ottomano, Gaopeng Ren, Kim E. Jelfs et al. |
|---|---|
| Primary category | cs.LG |
| Published | 10 July 2026 |
| Last updated at source | 2 October 2026 |
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