Deep generative models have unlocked another profound realm of human creativity. By
capturing and generalizing patterns within data, we have entered the epoch of all …

Natural data is redundant yet predominant architectures tile computation uniformly across
their input and output space. We propose the Recurrent Interface Networks (RINs), an …

Mainstream solutions to sequential recommendation represent items with fixed vectors.
These vectors have limited capability in capturing items' latent aspects and users' diverse …

In this paper, we introduce a novel dIffusion language modEl pre-training framework for text
generation, which we call GENIE. GENIE is a large-scale pre-trained diffusion language …

Diffusion models have achieved state-of-the-art synthesis quality on both visual and audio
tasks, and recent works further adapt them to textual data by diffusing on the embedding …

While diffusion models have achieved great success in generating continuous signals such
as images and audio, it remains elusive for diffusion models in learning discrete sequence …

Layout design is an important task in various design fields, including user interface,
document, and graphic design. As this task requires tedious manual effort by designers …

Combining discrete and continuous data is an important capability for generative models.
We present Discrete Flow Models (DFMs), a new flow-based model of discrete data that …

Given the great success that diffusion models have achieved in generating various types of
continuous data, including image, video and audio, there has been a growing interest in the …

Diffusion models are a kind of math-based model that were first applied to image generation.
Recently, they have drawn wide interest in natural language generation (NLG), a sub-field of …