Discrete diffusion language modeling by estimating the ratios of the data distribution
Despite their groundbreaking performance for many generative modeling tasks, diffusion
models have fallen short on discrete data domains such as natural language. Crucially …
models have fallen short on discrete data domains such as natural language. Crucially …
Tess: Text-to-text self-conditioned simplex diffusion
Diffusion models have emerged as a powerful paradigm for generation, obtaining strong
performance in various continuous domains. However, applying continuous diffusion …
performance in various continuous domains. However, applying continuous diffusion …
Generative flows on discrete state-spaces: Enabling multimodal flows with applications to protein co-design
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 …
We present Discrete Flow Models (DFMs), a new flow-based model of discrete data that …
Diffusion language models can perform many tasks with scaling and instruction-finetuning
The recent surge of generative AI has been fueled by the generative power of diffusion
probabilistic models and the scalable capabilities of large language models. Despite their …
probabilistic models and the scalable capabilities of large language models. Despite their …
Diffusion Guided Language Modeling
J Lovelace, V Kishore, Y Chen… - arXiv preprint arXiv …, 2024 - arxiv.org
Current language models demonstrate remarkable proficiency in text generation. However,
for many applications it is desirable to control attributes, such as sentiment, or toxicity, of the …
for many applications it is desirable to control attributes, such as sentiment, or toxicity, of the …
ParaGuide: Guided Diffusion Paraphrasers for Plug-and-Play Textual Style Transfer
Textual style transfer is the task of transforming stylistic properties of text while preserving
meaning. Target" styles" can be defined in numerous ways, ranging from single attributes …
meaning. Target" styles" can be defined in numerous ways, ranging from single attributes …
Amortizing intractable inference in diffusion models for vision, language, and control
Diffusion models have emerged as effective distribution estimators in vision, language, and
reinforcement learning, but their use as priors in downstream tasks poses an intractable …
reinforcement learning, but their use as priors in downstream tasks poses an intractable …
Simple and Effective Masked Diffusion Language Models
While diffusion models excel at generating high-quality images, prior work reports a
significant performance gap between diffusion and autoregressive (AR) methods in …
significant performance gap between diffusion and autoregressive (AR) methods in …
Diffusion of Thoughts: Chain-of-Thought Reasoning in Diffusion Language Models
Diffusion models have gained attention in text processing, offering many potential
advantages over traditional autoregressive models. This work explores the integration of …
advantages over traditional autoregressive models. This work explores the integration of …
Discrete Diffusion Language Model for Long Text Summarization
While diffusion models excel at conditional generating high-quality images, prior works in
discrete diffusion models were not evaluated on conditional long-text generation. In this …
discrete diffusion models were not evaluated on conditional long-text generation. In this …