[IJCAI'23] The official Github page of the paper "Diffusion Models for Non-autoregressive Text Generation: A Survey".
33
8 commits
updated Dec 21, 2023
A collection of papers related to text diffusion models.
The organization of papers refer to our survey 'Diffusion Models for Non-autoregressive Text Generation: A Survey' , which is accepted by IJCAI 2023 survey track.
If you find our survey useful for your research, please cite the following paper:
@article{li2023diffusion,
title={Diffusion Models for Non-autoregressive Text Generation: A Survey},
author={Li, Yifan and Zhou, Kun and Zhao, Wayne Xin and Wen, Ji-Rong},
journal={arXiv preprint arXiv:2303.06574},
year={2023}
}

Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
Emiel Hoogeboom et al. NeurIPS 2021. [Paper]
Diffusion-LM Improves Controllable Text Generation
Xiang Lisa Li et al. NeurIPS 2022. [Paper] [Code]
Composable Text Controls in Latent Space with ODEs
Guangyi Liu et al. arxiv 2022. [Paper] [Code]
DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models
Shansan Gong et al. ICLR 2023. [Paper] [Code]
SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control
Xiaochuang Han et al. arxiv 2022.[Paper] [Code]
Self-conditioned Embedding Diffusion for Text Generation
Robin Strudel et al. arxiv 2022. [Paper]
Continuous diffusion for categorical data
Sander Dieleman et al. arxiv 2022. [Paper]
Difformer: Empowering Diffusion Model on Embedding Space for Text Generation
Zhujin Gao et al. arxiv 2022. [Paper]
Latent Diffusion for Language Generation
Justin Lovelace et al. arxiv 2022. [Paper] [Code]
SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers
Hongyi Yuan et al. arxiv 2022. [Paper] [Code]
Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise
Zhenghao Lin et al. arxiv 2022. [Paper] [Code]
A Reparameterized Discrete Diffusion Model for Text Generation
Lin Zheng et al. arxiv 2023. [Paper] [Code]
DINOISER: Diffused Conditional Sequence Learning by Manipulating Noises
Jiasheng Ye et al. arxiv 2023. [Paper] [Code]
GlyphDiffusion: Text Generation as Image Generation
Junyi Li et al. arxiv 2023. [Paper]
DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLM
Weijie Xu et al. Findings of EMNLP 2023. [Paper]

Structured Denoising Diffusion Models in Discrete State-Spaces
Jacob Austin et al. NeurIPS 2021. [Paper]
DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models
Zhengfu He et al. arXiv 2022. [Paper] [Code]
Diff-Glat: Diffusion Glancing Transformer for Parallel Sequence to Sequence Learning
Lihua Qian et al. arxiv 2022. [Paper]
Diffusion-NAT: Self-Prompting Discrete Diffusion for Non-Autoregressive Text Generation
Kun Zhou et al. arxiv 2023. [Paper]
[IJCAI'23] The official Github page of the paper "Diffusion Models for Non-autoregressive Text Generation: A Survey".
33
8 commits
updated Dec 21, 2023
A collection of papers related to text diffusion models.
The organization of papers refer to our survey 'Diffusion Models for Non-autoregressive Text Generation: A Survey' , which is accepted by IJCAI 2023 survey track.
If you find our survey useful for your research, please cite the following paper:
@article{li2023diffusion,
title={Diffusion Models for Non-autoregressive Text Generation: A Survey},
author={Li, Yifan and Zhou, Kun and Zhao, Wayne Xin and Wen, Ji-Rong},
journal={arXiv preprint arXiv:2303.06574},
year={2023}
}

Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions
Emiel Hoogeboom et al. NeurIPS 2021. [Paper]
Diffusion-LM Improves Controllable Text Generation
Xiang Lisa Li et al. NeurIPS 2022. [Paper] [Code]
Composable Text Controls in Latent Space with ODEs
Guangyi Liu et al. arxiv 2022. [Paper] [Code]
DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models
Shansan Gong et al. ICLR 2023. [Paper] [Code]
SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control
Xiaochuang Han et al. arxiv 2022.[Paper] [Code]
Self-conditioned Embedding Diffusion for Text Generation
Robin Strudel et al. arxiv 2022. [Paper]
Continuous diffusion for categorical data
Sander Dieleman et al. arxiv 2022. [Paper]
Difformer: Empowering Diffusion Model on Embedding Space for Text Generation
Zhujin Gao et al. arxiv 2022. [Paper]
Latent Diffusion for Language Generation
Justin Lovelace et al. arxiv 2022. [Paper] [Code]
SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers
Hongyi Yuan et al. arxiv 2022. [Paper] [Code]
Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise
Zhenghao Lin et al. arxiv 2022. [Paper] [Code]
A Reparameterized Discrete Diffusion Model for Text Generation
Lin Zheng et al. arxiv 2023. [Paper] [Code]
DINOISER: Diffused Conditional Sequence Learning by Manipulating Noises
Jiasheng Ye et al. arxiv 2023. [Paper] [Code]
GlyphDiffusion: Text Generation as Image Generation
Junyi Li et al. arxiv 2023. [Paper]
DeTiME: Diffusion-Enhanced Topic Modeling using Encoder-decoder based LLM
Weijie Xu et al. Findings of EMNLP 2023. [Paper]

Structured Denoising Diffusion Models in Discrete State-Spaces
Jacob Austin et al. NeurIPS 2021. [Paper]
DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models
Zhengfu He et al. arXiv 2022. [Paper] [Code]
Diff-Glat: Diffusion Glancing Transformer for Parallel Sequence to Sequence Learning
Lihua Qian et al. arxiv 2022. [Paper]
Diffusion-NAT: Self-Prompting Discrete Diffusion for Non-Autoregressive Text Generation
Kun Zhou et al. arxiv 2023. [Paper]