Diffusion Language Model Training

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54 papers13 papers in the last four weeks, up 30% on the four weeks before. 0.1% of all new papers.

PBPO: Prefix-Block Policy Optimization for Diffusion Language Models
Nov 5, 2026Katherine Tieu, Dongqi Fu, Si Zhang +6Diffusion Language Model Training RL for Diffusion Models
Meta · University of Illinois Urbana-Champaign
Continued Training of Continuous Language Flows with Token Identity Squared Supervision
Nov 5, 2026Jiawei Jiang, Zhaoxiang Zang, Zhengtao YuDiffusion Language Model Training Continuous Diffusion Language Models
Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China · Key Laboratory of Artificial Intelligence in Yunnan Province, Kunming University of Science and Technology, Kunming, China
BYOD: Build Your Own DLM - Efficient Autoregressive-to-Diffusion Language Model Conversion
Oct 30, 2026Ruurd J. A. Kuiper, Robert A. BagheriDiffusion Language Models Diffusion Language Model Training
Julius Center for Health Sciences and Primary Care University Medical Center Utrecht · Department of Methodology and Statistics Utrecht University, The Netherlands
Self-Regularized Flow Language Models
Oct 27, 2026Theodoros Kouzelis, Spyros Gidaris, Nikos KomodakisDiffusion Language Model Training Continuous Diffusion Language Models
Archimedes, Athena RC · National Technical University of Athens · University of Crete +1
TDLM: Adaptive Temporal Integration for Diffusion Language Models
Oct 27, 2026Bohang Sun, Max Zhu, Francesco Caso +3Diffusion Language Models Diffusion Language Model Inference
Department of Computer Science and Technology, University of Cambridge · Department of Engineering Science, University of Oxford
Nemotron-Labs-Diffusion-Uni: Elastic Self-Refining Unified Diffusion LLM with Cross-Paradigm On-Policy Distillation
Oct 27, 2026Shufan Li, Hanrong Ye, Greg Heinrich +5Diffusion VLMs Diffusion Language Models
DTCA: Denoising Token Credit Assignment for Reinforcement Learning in Diffusion Language Models
Oct 26, 2026Hongze Chen, Miao Pan, Lizhou Liang +7Diffusion Language Model Training RL for Diffusion Models
Zhejiang University · National University of Singapore · SAP
How To Build A Modern Diffusion Language Model
Oct 24, 2026Volodymyr Kuleshov, Marianne Arriola, Yair Schiff +2Diffusion Language Models Diffusion Language Model Inference
Cornell University, USA
Random Remasking Scales Masked Diffusion Inference
Oct 22, 2026Zhaoyi Zhou, Frank Wu, Andrea ZanetteMasked Diffusion Models Diffusion Language Model Inference
Carnegie Mellon University
Loopholing All the Way: Language Modeling with pure Self-Conditioning
Oct 21, 2026Adrien Deschenaux, Nadezhda Ilieva, Justin Deschenaux +6Diffusion Language Models Continuous Diffusion Language Models
EPFL, Lausanne, Switzerland · University of Basel, Switzerland · ELLIS Institute Tübingen, MPI for Intelligent Systems, Tübingen AI Center, Germany +1
Looped Uniform Diffusion Language Models
Oct 21, 2026Saiteja Utpala, Chieh-Hsin Lai, Yuki Mitsufuji +1Diffusion Language Models Diffusion Language Model Training
MBZUAI · Sony Group Corporation · MIT
Hierarchical Masked Diffusion Language Models
Oct 21, 2026Parul Gupta, Satwik, Avni Aggarwal +5Masked Diffusion Models Diffusion Language Model Decoding
Indian Institute of Technology Delhi · IBM Research
Noise Your Prompt: Noising Conditioning Tokens in Continuous Diffusion Language Models
Oct 6, 2026Justin JungDiffusion Language Model Training Continuous Diffusion Language Models
Lateral Intelligence
Enhancing Diffusion Language Models with Autoregressive Post-Training Weights
Oct 6, 2026Yiming Qin, Ke Wang, Amel Abdelraheem +2Diffusion Language Model Training Model Merging
EPFL, Lausanne, Switzerland
Representation-Space MMD for Diffusion Language Models
Oct 5, 2026Ilya Drobyshevskiy, Ilia Sudakov, Maksim Semenov +7Diffusion Model Alignment Maximum Mean Discrepancy
Yandex Research · HSE University · T-Tech +3
ALoDLM: Adaptively Looped Diffusion Language Models
Oct 3, 2026Liancheng Fang, Zhuowei Li, Youngeun Kim +10Adaptive Computation for Diffusion Models Diffusion Language Models
University of Illinois Chicago · Amazon AGI · Korea University
Scaling and Distilling Text Embeddings for Better Diffusibility
Oct 1, 2026Zekai Zhang, Yunjie Tian, Yanjin He +4Word Embeddings Language Model Distillation
University of Michigan
Clock Diffusion: Efficient Semi-Autoregressive Continuous Diffusion Language Models
Oct 1, 2026Yair Schiff, Omer Belhasin, Roy Uziel +7Diffusion Language Model Inference Language Modeling
NVIDIA · Cornell University
Distribution Matching Distillation for Continuous Diffusion Language Models
Sep 30, 2026Paul Le Van Kiem, Dario Shariatian, Umut Simsekli +1Continuous Diffusion Language Models Diffusion Language Model Distillation
Inria, PSL Research University · Cohere · CMAP, Ecole Polytechnique
Alpha Diffusion Language Models: Factorization Alone Is Not the Problem
Sep 29, 2026Nikita Gushchin, Dmitry Baranchuk, Alexander KorotinDiffusion Language Models Diffusion Language Model Training
Applied AI Institute, Moscow, Russia · AXXX, Russia · Yandex Research
Time-Anchored Diffusion Language Models: Latent-Space Caching for Fast Generation
Sep 29, 2026Joel Anto Paul, Litu Rout, Aditya Akella +1Diffusion Language Model Training Diffusion Language Model Inference
UT Austin
One Latent, Many Tokens: Jointly Learning Compressed Embeddings for Efficient Language Diffusion
Sep 27, 2026Yulin Yuan, Ying Zhang, Xiangming MengDiffusion Language Model Inference Diffusion Model Compression
Zhejiang University · University of Cambridge · ZJU-UIUC Institute, Zhejiang University
Towards Efficient Reasoning: Learning Causal Shortcuts for Diffusion Language Models
Sep 23, 2026Dian Jin, Kairong Han, Baohong Li +5Diffusion Language Model Training Efficient Language Model Reasoning
Zhejiang University · Shanghai AI Laboratory
Block Parallelism For Efficient Distributed Long-Context Diffusion Language Model Training
Sep 16, 2026Tarun Suresh, Pranshu Chaturvedi, Hangoo Kang +4Communication-Efficient Distributed Training Long-Context Language Modeling
Stanford University
DA-DLM: Explicitly Modeling Token Dependencies in Diffusion Language Models
Sep 14, 2026Pengyu Ji, Zichen Zhang, Xiang Hu +1Non-Autoregressive Text Generation Diffusion Language Model Decoding
‡School of Information Science and Technology, ShanghaiTech University · §Shanghai Engineering Research Center of Intelligent Vision and Imaging · ¶Tencent
A Ticket from Marginals to Joints: Coupled-Noise Distillation for One-Step Block Generation in Diffusion Language Models
Sep 6, 2026Lin YaoOne-Step Generative Modeling Diffusion Language Models
School of Computer Science, Shanghai Jiao Tong University, Shanghai, 200240, China · Zhongguancun Academy, Beijing, 100097, China
SelFusion: Self-distillation for Diffusion Language Models
Aug 24, 2026Hyeongsoo Lim, Jinyoung Kim, Eunseo Seo +2Diffusion Language Model Training Diffusion Language Models
Department of Artificial Intelligence, Chung-Ang University
DiffusionGemma Technical Report
Jul 31, 2026DiffusionGemma Team, Adrien Ali Taïga, James Assiene +41Diffusion Language Model Decoding Blockwise Diffusion Language Models
Adaptive Block Diffusion: Resolving Training-Inference Mismatch in Diffusion Language Models
Jun 28, 2026Gagan JainDiffusion Language Model Training Blockwise Diffusion Language Models
Work done while at Microsoft AI.
Sumi: Open Uniform Diffusion Language Model from Scratch
Jun 17, 2026Mengyu Ye, Keito Kudo, Wataru Ikeda +3Language Model Pretraining Diffusion Language Models
1Tohoku University

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PBPO: Prefix-Block Policy Optimization for Diffusion Language Models

Katherine Tieu, Dongqi Fu, Si Zhang, Hanqing Zeng+5

Meta · University of Illinois Urbana-Champaign

Diffusion Language Model Training RL for Diffusion Models Blockwise Diffusion Language Models

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Diffusion Large Language Models (dLLMs) commonly decode responses by proceeding autoregressively across blocks while iteratively denoising multiple tokens within each block. This structure makes block-level policy optimization a natural adaptation of autoregressive policy optimization. However, the exact likelihood of a completed block is intractable because it marginalizes over the intermediate states and reveal orders of the denoising process. To realize the block-level formulation, we construct a prefix-block state and use a single model evaluation to define a factorized one-step surrogate for the block likelihood. The resulting block surrogate ratio is a product of its token surrogate ratios, allowing variation at individual positions to propagate across the entire block before clipping. We therefore introduce Prefix-Block Policy Optimization (PBPO), which preserves block-level conditioning but applies surrogate importance weighting and clipping separately to each token. PBPO further diversifies repeated updates by resampling corrupted views of the prompt and revealed prefix, a design motivated by masked-dLLM pre-training. Under our analysis assumptions, block-product weighting amplifies the variance of gradient contributions relative to token-local weighting. Across two LLaDA-family initializations, six benchmarks, and three generation lengths, PBPO achieves competitive performance against existing dLLM RL methods.