4 papers
Discrete Flow Maps
Peter Potaptchik, Jason Yim, Adhi Saravanan +3
The sequential nature of autoregressive next-token prediction imposes a fundamental speed limit on large language models. While continuous flow models offer a path to parallel gene…
Hierarchical protein backbone generation with latent and structure diffusion
Jason Yim, Marouane Jaakik, Ge Liu +5
We propose a hierarchical protein backbone generative model that separates coarse and fine-grained details. Our approach called LSD consists of two stages: sampling latents which a…
ProtComposer: Compositional Protein Structure Generation with 3D Ellipsoids
Hannes Stark, Bowen Jing, Tomas Geffner +4
We develop ProtComposer to generate protein structures conditioned on spatial protein layouts that are specified via a set of 3D ellipsoids capturing substructure shapes and semant…
Generator Matching: Generative modeling with arbitrary Markov processes
Peter Holderrieth, Marton Havasi, Jason Yim +6
We introduce Generator Matching, a modality-agnostic framework for generative modeling using arbitrary Markov processes. Generators characterize the infinitesimal evolution of a Ma…