# Discrete and text diffusion Area: [Diffusion models](https://mlsanity.com/diffusion/index.md). HTML: https://mlsanity.com/diffusion/discrete-and-text-diffusion/ ## Key facts - Discrete and text diffusion: 681 papers on arXiv since 2021 (data through 7 Oct 2026). - 353 of its 681 mapped papers (52%) cite “Large Language Diffusion Models” (2025, arXiv 2502.09992). - 351 of its 681 mapped papers (52%) cite “Simple and Effective Masked Diffusion Language Models” (2024, arXiv 2406.07524). - 78 new papers 17 Sep–7 Oct. ## Most cited here - [Large Language Diffusion Models](https://mlsanity.com/paper/2502.09992/) (2025), cited by 353 papers here - [Simple and Effective Masked Diffusion Language Models](https://mlsanity.com/paper/2406.07524/) (2024), cited by 351 papers here - [Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution](https://mlsanity.com/paper/2310.16834/) (2023), cited by 316 papers here - [Simplified and Generalized Masked Diffusion for Discrete Data](https://mlsanity.com/paper/2406.04329/) (2024), cited by 286 papers here - [Dream 7B: Diffusion Large Language Models](https://mlsanity.com/paper/2508.15487/) (2025), cited by 276 papers here - [Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models](https://mlsanity.com/paper/2503.09573/) (2025), cited by 208 papers here - [Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data](https://mlsanity.com/paper/2406.03736/) (2024), cited by 198 papers here - [Scaling Diffusion Language Models via Adaptation from Autoregressive Models](https://mlsanity.com/paper/2410.17891/) (2024), cited by 153 papers here - [DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models](https://mlsanity.com/paper/2210.08933/) (2022), cited by 141 papers here - [Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions](https://mlsanity.com/paper/2502.06768/) (2025), cited by 125 papers here ## New (17 Sep–7 Oct) - [Unrolled Flow Models for Reasoning](https://mlsanity.com/paper/2610.09759/) (2026-10-07) - [Beyond Token Revision: Investigating Mask-and-Replace Diffusion for Zero-Shot Text-to-Speech](https://mlsanity.com/paper/2610.09448/) (2026-10-07) - [Efficient Reasoning with Flow Language Models](https://mlsanity.com/paper/2610.09416/) (2026-10-07) - [Denoising Blocks, Not Tokens: Efficient Compressed Continuous Diffusion with Branching Token Realization](https://mlsanity.com/paper/2610.09311/) (2026-10-07) - [Noise Your Prompt: Noising Conditioning Tokens in Continuous Diffusion Language Models](https://mlsanity.com/paper/2610.09145/) (2026-10-06) - [Denoising Hierarchical Representations: Joint Continuous Diffusion for Language Modeling](https://mlsanity.com/paper/2610.08738/) (2026-10-06) - [Disentangling Paradigm, Identifier, and Decoding in Generative Retrieval](https://mlsanity.com/paper/2610.08716/) (2026-10-06) - [Enhancing Diffusion Language Models with Autoregressive Post-Training Weights](https://mlsanity.com/paper/2610.08108/) (2026-10-06) - [SoloQ: Calibration-Free Quantization for Diffusion Language Models](https://mlsanity.com/paper/2610.07121/) (2026-10-05) - [Representation-Space MMD for Diffusion Language Models](https://mlsanity.com/paper/2610.06648/) (2026-10-05) - [Noise Out, Bias In: Targeted Bias Injection in Diffusion Language Models via Closed-Loop Activation Steering](https://mlsanity.com/paper/2610.05894/) (2026-10-05) - [Mask-Guided KV Cache Eviction in Block Diffusion Language Models](https://mlsanity.com/paper/2610.06996/) (2026-10-04) - [Towards Unbiased On-Policy Distillation for Block Diffusion Language Models](https://mlsanity.com/paper/2610.05373/) (2026-10-04) - [Bayesian Entropy-based Reordering for Calibrated Diffusion Language Models](https://mlsanity.com/paper/2610.05125/) (2026-10-04) - [SpecFold: Folding Multi-Branch Redundancy for Faster Speculative Decoding in Diffusion Language Models](https://mlsanity.com/paper/2610.04875/) (2026-10-04) - [Stabilizing language models under continual learning via condition-anchored distillation](https://mlsanity.com/paper/2610.06940/) (2026-10-03) - [ALoDLM: Adaptively Looped Diffusion Language Models](https://mlsanity.com/paper/2610.04198/) (2026-10-03) - [Pivot-SD: Efficient Self-Distillation for Masked Diffusion Language Models](https://mlsanity.com/paper/2610.03665/) (2026-10-02) - [Preserving Mathematical Reasoning in Compressed Diffusion Language Models via Trajectory-Aware Low-Rank Approximation](https://mlsanity.com/paper/2610.03326/) (2026-10-02) - [Refinement Buys Intelligibility, Search Buys Identity: What Test-Time Compute Buys in Masked-Diffusion TTS](https://mlsanity.com/paper/2610.03320/) (2026-10-02) - [Large Language Continuous Diffusion Models](https://mlsanity.com/paper/2610.02665/) (2026-10-02) - [Context-Tower Conversion Preserves Generation While Freezing Retains Knowledge: Low-Budget AR-to-Diffusion Conversion of MoE LLMs](https://mlsanity.com/paper/2610.02657/) (2026-10-02) - [Hierarchical Continuous Diffusion Language Models](https://mlsanity.com/paper/2610.02193/) (2026-10-01) - [SALD: Self-Referenced Advantage Learning for Diffusion Models](https://mlsanity.com/paper/2610.01496/) (2026-10-01) - [ITC-MoE: Importance-guided Token-aware Compression for MoE Diffusion Language Models](https://mlsanity.com/paper/2610.01296/) (2026-10-01) - [Know When to Hold 'em: Correct-Token Retention in Uniform-State Diffusion Language Models](https://mlsanity.com/paper/2610.01275/) (2026-10-01) - [Temporally-Resolved Token Attribution Reveals the Generation Dynamics of Diffusion Language Models](https://mlsanity.com/paper/2610.01177/) (2026-10-01) - [Scaling and Distilling Text Embeddings for Better Diffusibility](https://mlsanity.com/paper/2610.01016/) (2026-10-01) - [Two Clocks in Diffusion MLLMs: When Answers Stabilize Before Rationales Unfold](https://mlsanity.com/paper/2610.00953/) (2026-10-01) - [Clock Diffusion: Efficient Semi-Autoregressive Continuous Diffusion Language Models](https://mlsanity.com/paper/2610.00894/) (2026-10-01)