18 citations · 19 across the 5 of their papers we have counts for
5 papers
What Does a Discrete Diffusion Model Learn? One Reverse Process in Three Coordinates
Rodrigo Casado Noguerales, Bernhard Schölkopf, Thomas Hofmann +1
What does a discrete diffusion model actually learn? The literature trains denoisers, bridge plug-ins, and concrete scores, each deriving its own ELBO objective under different con…
Scaling Behavior of Discrete Diffusion Language Models
Dimitri von Rütte, Janis Fluri, Omead Pooladzandi +3
Modern LLM pre-training consumes vast amounts of compute and training data, making the scaling behavior, or scaling laws, of different models a key distinguishing factor. Discrete…
Generalized Interpolating Discrete Diffusion
Dimitri von Rütte, Janis Fluri, Yuhui Ding +3
While state-of-the-art language models achieve impressive results through next-token prediction, they have inherent limitations such as the inability to revise already generated to…
FIGARO: Generating Symbolic Music with Fine-Grained Artistic Control
Dimitri von Rütte, Luca Biggio, Yannic Kilcher +1
Generating music with deep neural networks has been an area of active research in recent years. While the quality of generated samples has been steadily increasing, most methods ar…
On the effectiveness of Randomized Signatures as Reservoir for Learning Rough Dynamics
Enea Monzio Compagnoni, Anna Scampicchio, Luca Biggio +3
Many finance, physics, and engineering phenomena are modeled by continuous-time dynamical systems driven by highly irregular (stochastic) inputs. A powerful tool to perform time se…