mlsanityData to 7 Oct 2026

Diffusion Models in NLP: A Survey

arXiv 2303.07576 ↗First posted 14 Mar 2023cs.CL cs.AIcited by 16

On the map: Diffusion models → Discrete and text diffusion

Abstract (arXiv)

Diffusion models have become a powerful family of deep generative models, with record-breaking performance in many applications. This paper first gives an overview and derivation of the basic theory of diffusion models, then reviews the research results of diffusion models in the field of natural language processing, from text generation, text-driven image generation and other four aspects, and analyzes and summarizes the relevant literature materials sorted out, and finally records the experience and feelings of this topic literature review research.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Placed in Discrete and text diffusion, one of 14 directions in Diffusion models. Builds on 47 of its 59 references that are in the map. First posted on arXiv 14 Mar 2023.

Builds on

47 of 59 references.

Closest ancestors · 12

Same direction, newest first

  1. 2023DINOISER: Diffused Conditional Sequence Learning by Manipulating Noises20 Feb
  2. 2023A Reparameterized Discrete Diffusion Model for Text Generation11 Feb
  3. 2022Text Generation with Diffusion Language Models: A Pre-training Approach with Continuous Paragraph Denoise22 Dec
  4. 2022SeqDiffuSeq: Text Diffusion with Encoder-Decoder Transformers20 Dec
  5. 2022Latent Diffusion for Language Generation19 Dec
  6. 2022Empowering Diffusion Models on the Embedding Space for Text Generation19 Dec
  7. 2022DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models28 Nov
  8. 2022Self-conditioned Embedding Diffusion for Text Generation8 Nov
  9. 2022SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular Control31 Oct
  10. 2022DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models17 Oct
  11. 2022Latent Diffusion Energy-Based Model for Interpretable Text Modeling13 Jun
  12. 2021Zero-Shot Translation using Diffusion Models2 Nov

Other references · 35

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  6. 2020Denoising Diffusion Implicit Modelscited by 9,655
  7. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  8. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  9. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  10. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  11. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  12. 2022Generative Adversarial Networkscited by 5,603
23 more
  1. 2013Auto-Encoding Variational Bayescited by 3,980
  2. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  3. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  4. 2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,665
  5. 2018Glow: Generative Flow with Invertible 1x1 Convolutionscited by 1,539
  6. 2022Diffusion-LM Improves Controllable Text Generationcited by 1,006
  7. 2021Blended Diffusion for Text-driven Editing of Natural Imagescited by 924
  8. 2021Vector Quantized Diffusion Model for Text-to-Image Synthesiscited by 773
  9. 2017Masked Autoregressive Flow for Density Estimationcited by 680
  10. 2021Argmax Flows and Multinomial Diffusion: Learning Categorical Distributionscited by 566
  11. 2020Pre-trained Models for Natural Language Processing: A Surveycited by 504
  12. 2021Label-Efficient Semantic Segmentation with Diffusion Modelscited by 495
  13. 2021MAUVE: Measuring the Gap Between Neural Text and Human Text using Divergence Frontierscited by 466
  14. 2022Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioningcited by 362
  15. 2022Diffsound: Discrete Diffusion Model for Text-to-sound Generationcited by 256
  16. 2021More Control for Free! Image Synthesis with Semantic Diffusion Guidancecited by 211
  17. 2022ProDiff: Progressive Fast Diffusion Model For High-Quality Text-to-Speechcited by 147
  18. 2022Semantic Image Synthesis via Diffusion Modelscited by 131
  19. 2021Step-unrolled Denoising Autoencoders for Text Generationcited by 102
  20. 2020Trading Off Diversity and Quality in Natural Language Generationcited by 94
  21. 2021Guided-TTS: A Diffusion Model for Text-to-Speech via Classifier Guidancecited by 84
  22. 2022Text-Guided Synthesis of Artistic Images with Retrieval-Augmented Diffusion Modelscited by 63
  23. 2020A Systematic Characterization of Sampling Algorithms for Open-ended Language Generationcited by 28

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 3; 2024: 9; 2025: 2; 2026: 2.

16 papers.

Sort:

By area:

  1. 2023On the Design Fundamentals of Diffusion Models: A Surveycited by 59
  2. 2023Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimizationcited by 56
  3. 2024Attacks and Defenses for Generative Diffusion Models: A Comprehensive Surveycited by 32
  4. 2024Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectivescited by 27
  5. 2024A Survey on Diffusion Models for Recommender Systemscited by 20
  6. 2024A Directional Diffusion Graph Transformer for Recommendationcited by 9
  7. 2025Diffusion and Flow Matching Models for Tabular Data: A Surveycited by 8
  8. 2023A Comprehensive Survey on Generative Diffusion Models for Structured Datacited by 7
  9. 2024Data Augmentation via Latent Diffusion for Saliency Predictioncited by 5
  10. 2024Let's Rectify Step by Step: Improving Aspect-based Sentiment Analysis with Diffusion Modelscited by 2
  11. 2024MaskPure: Improving Defense Against Text Adversaries with Stochastic Purificationcited by 2
  12. 2025Diffusion Models for Reinforcement Learning: Foundations, Taxonomy, and Developmentcited by 2
4 more
  1. 2024Resistive Memory-based Neural Differential Equation Solver for Score-based Diffusion Modelcited by 0
  2. 2024DiffPoGAN: Diffusion Policies with Generative Adversarial Networks for Offline Reinforcement Learningcited by 0
  3. 2026TooBad: Backdoor Diffusion Models with Ultra-Low Poison Rate and Imperceptible Triggercited by 0
  4. 2026Eval4DiRec: A Unified and Systematic Evaluation Framework for Diffusion-based Recommender Systemscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023A Survey of Diffusion Models in Natural Language Processing
  2. 2025Discrete Diffusion Models for Language Generation
  3. 2023Diffusion Models for Non-autoregressive Text Generation: A Survey
  4. 2024Scaling Diffusion Language Models via Adaptation from Autoregressive Models
  5. 2022Diffusion Models: A Comprehensive Survey of Methods and Applications
  6. 2023AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
  7. 2023Text-to-image Diffusion Models in Generative AI: A Survey
  8. 2026Towards Latent Diffusion Suitable For Text