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This is the official implementation of the paper: A Cheaper and Better Diffusion Language Model with Soft-Masked Noise.
Boyuan Chen 1 , Diego Martí Monsó 2 , Yilun Du 1 , Max Simchowitz 1 , Russ Tedrake 1 , Vincent Sitzmann 1 1 MIT 2 Technical University of Munich
We introduce Text-to-text Self-conditioned Simplex Diffusion (TESS), a text diffusion model that is fully non-autoregressive, employs a new form of self-conditioning, and applies the diffusion process on the logit simplex space rather than the typical learned embedding space.
This repository contains the official implementation of paper DINOISER: Diffused Conditional Sequence Learning by Manipulating Noises (TACL & ACL2024 Oral).
The main features of yegcjs/dinoiser are: Continuous Diffusion Models, Custom Noise Processes.
Open-source alternatives to yegcjs/dinoiser include: amazon-science/masked-diffusion-lm — This is the official implementation of the paper: A Cheaper and Better Diffusion Language Model with Soft-Masked Noise. ashaba1in/smoothie — Paper: https://arxiv.org/pdf/2505.18853. buoyancy99/diffusion-forcing — Boyuan Chen 1 , Diego Martí Monsó 2 , Yilun Du 1 , Max Simchowitz 1 , Russ Tedrake 1 , Vincent Sitzmann 1 1 MIT 2… bytedance-seed/cola-dlm — Continuous Latent Diffusion Language Model — a hierarchical latent-space text diffusion model with a block-causal DiT… david3684/flm — Flow Map Language Models: One-step Language Modeling via Continuous Denoising. allenai/tess-diffusion — We introduce Text-to-text Self-conditioned Simplex Diffusion (TESS), a text diffusion model that is fully…
