Diffusion Language Model Inference

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26 papers in the last four weeks, up 767% on the four weeks before. 0.3% of all new papers.

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Latest papers 108

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AsyncLane: Decoupling Refinement from Advancement in Diffusion Language Model Decoding
Jun 7, 2026Yingxuan Ren, Yuxuan Lou, Yong Liu +4LLM Inference Scheduling Blockwise Diffusion Language Models
1National University of Singapore · University of Southampton
Self-Augmenting Retrieval for Diffusion Language Models
Jun 4, 2026Paul Jünger, Justin Lovelace, Linxi Zhao +2Multi-Hop QA Retrieval-Augmented Generation
Department of Computer Science, Cornell University.
SAID: Accelerating Diffusion-Based Language Models via Scaffold-Aware Iterative Decoding
Jun 3, 2026Na Li, Chengda Wang, Mingju Gao +1Diffusion Language Model Inference Diffusion Language Model Decoding
School of Computer Science, Peking University
D^2SD: Accelerating Speculative Decoding with Dual Diffusion Draft Models
Jun 3, 2026Liyuan Zhang, Jiarui Zhang, Jinwei Yao +6Speculative Decoding for Diffusion Language Models Speculative Decoding
Peking University · Tsinghua University · HKUST +2
SimSD: Simple Speculative Decoding in Diffusion Language Models
Jun 1, 2026Junxia Cui, Haotian Ye, Runchu Tian +9Masked Diffusion Models Speculative Decoding for Diffusion Language Models
University of California San Diego · University of Illinois Urbana-Champaign · 3Google +1
FLARE: Diffusion for Hybrid Language Model
Jun 1, 2026Yuchen Zhu, Jing Shi, Chongjian Ge +9Diffusion Model Serving Diffusion Language Model Inference
1Adobe Research · 2Georgia Institute of Technology
WaveFilter: Enhancing the Long-Context Capability of Diffusion LLMs via Wavelet-Guided KV Cache Filtering
May 30, 2026Jinnan Yang, Yan Wang, Zhen Bi +5Long-Context Language Model Inference Diffusion Language Model Inference
Nanjing University of Science and Technology · Alibaba Group · Huzhou Normal University +1
What Gets Unmasked First? Trajectory Analysis of Diffusion Models for Graph-to-Text Generation
May 29, 2026Qing Wang, Jacob Devasier, Chengkai LiMasked Diffusion Models LLM Fine-Tuning
The University of Texas at Arlington
dMoE: dLLMs with Learnable Block Experts
May 29, 2026Sicheng Feng, Zigeng Chen, Gongfan Fang +2Mixture-of-Experts Language Models Memory-Efficient Inference
National University of Singapore
DLM-SWAI: Steering Diffusion Language Models Before They Unmask
May 28, 2026Hyeseon An, Yo-Sub HanControllable Text Generation Diffusion Language Model Inference
Department of Computer Science, Yonsei University, Seoul, South Korea
Cluster-Level Attention-Guided Parallel Decoding for Masked Diffusion Language Models
May 28, 2026Heqiang Qi, Wei Huang, Mingyuan Bai +1Masked Diffusion Models Diffusion Language Model Inference
Zhejiang University · RIKEN Center for Advanced Intelligence Project · The Institute of Statistical Mathematics +1
BlockBatch: Multi-Scale Consensus Decoding for Efficient Diffusion Language Model Inference
May 28, 2026Xiaoyou Wu, Cheng-Jhih Shih, Binfei Ji +2Blockwise Diffusion Language Models Diffusion Language Model Inference
Georgia Institute of Technology
Dynamic-dLLM: Dynamic Cache-Budget and Adaptive Parallel Decoding for Training-Free Acceleration of Diffusion LLM
May 27, 2026Tianyi Wu, Xiaoxi Sun, Yanhua Jiao +5Diffusion Language Model Inference Diffusion Language Model Decoding
*Equal contribution. The work is done during Tianyi’s internship at CBG Celia DeviceAI Team, Huawei. · 1Harbin Institute of Technology, Shenzhen · 2Huawei +1
Enabling KV Caching of Shared Prefix for Diffusion Language Models
May 26, 2026Younghun Go, Jaehoon Han, Changyong Shin +2KV Caching KV-Cache Management
Korea University, South Korea
Looped Diffusion Language Models
May 25, 2026Sanghyun Lee, Chunsan Hong, Seungryong Kim +3Masked Diffusion Models Diffusion Language Model Inference
1KAIST · 2KRAFTON · University of California, Berkeley
Triplet-Block Diffusion RWKV
May 25, 2026Ke Lin, Yiyang Luo, Zhaolong Su +2Diffusion Language Model Inference Recurrent Transformers
William & Mary · HKUST · Cornell
DiLaDiff: Distilled Latent-Augmented Diffusion for Language Modeling
May 22, 2026Jean-Marie Lemercier, Tomas Geffner, Karsten Kreis +3Masked Diffusion Models Diffusion Language Model Inference
NVIDIA
Learned Relay Representations for Forward-Thinking Discrete Diffusion Models
May 21, 2026Benjamin Rozonoyer, Jacopo Minniti, Dhruvesh Patel +4Masked Diffusion Models Diffusion Language Model Inference
University of Massachusetts Amherst · University of Toronto · Stanford University +3
PulseCol: Periodically Refreshed Column-Sparse Attention for Accelerating Diffusion Language Models
May 20, 2026Yanyi Lyu, Letian Chen, Futing Sun +3Self-Attention Diffusion Language Model Inference
Harbin Institute of Technology (Shenzhen)
TIDE: Efficient and Lossless MoE Diffusion LLM Inference with I/O-aware Expert Offload
May 19, 2026Zhiben Chen, Youpeng Zhao, Yang Sui +2Expert Offloading LLM Inference Scheduling
University of Central Florida · Rice University
Elastic-dLLM: Position Preserving Context Compression and Augmentation of Diffusion LLMs
May 18, 2026Junyi Wu, Tianchen Zhao, Shaoqiu Zhang +3Masked Diffusion Models Long-Context Language Modeling
Tsinghua University · Shanghai Jiao Tong University · Infinigence AI
Prefix-Adaptive Block Diffusion for Efficient Document Recognition
May 16, 2026Mingxu Chai, Ziyu Shen, Chenyu Liu +9Diffusion Language Model Inference Diffusion Model Caching
Computation and Artificial Intelligence Innovative College, Fudan University, Shanghai, China · Shanghai Innovation Institute, Shanghai, China · ByteDance, Shanghai, China
PSD: Pushing the Pareto Frontier of Diffusion LLMs via Parallel Speculative Decoding
May 15, 2026Shengyin Sun, Yiming Li, Renxi Liu +7Masked Diffusion Models Speculative Decoding for Diffusion Language Models
Department of Computer Science City University of Hong Kong · Huawei Technologies · City University of Hong Kong
Factorization-Error-Free Discrete Diffusion Language Model via Speculative Decoding
May 14, 2026Xun Fang, Yunchen Li, Hang Yuan +1Speculative Decoding for Diffusion Language Models Diffusion Language Model Inference
East China Normal University · Beijing Zhongguancun Academy
Adaptive Steering and Remasking for Safe Generation in Diffusion Language Models
May 13, 2026Yejin Lee, Ungsik Kim, Yo-Sub HanAdversarial Attacks on LLMs Diffusion Language Model Inference
Department of Computer Science Yonsei University Seoul, Republic of Korea
Orthrus: Memory-Efficient Parallel Token Generation via Dual-View Diffusion
May 12, 2026Chien Van Nguyen, Chaitra Hegde, Van Cuong Pham +3Language Model Decoding Diffusion Language Model Inference
University of Oregon · Google DeepMind · Adobe Research
Multi-Token Residual Prediction
May 12, 2026Yufeng Xu, Zishuo Bao, Qian Wang +6Masked Diffusion Models Multi-Token Prediction
New York University · New York University Shanghai · Nous Research +1
TAD: Temporal-Aware Trajectory Self-Distillation for Fast and Accurate Diffusion LLM
May 10, 2026Haoyang Zhou, Li Kong, Shijie Ren +4Diffusion Model Distillation Diffusion Language Model Inference
Gaoling School of Artificial Intelligence, Renmin University of China · Ant Group
Path-Dependent Denoising: A Non-Conservative Field Perspective on Order Collapse in Diffusion Language Models
May 10, 2026Jeonseong KimDiffusion Language Model Inference Diffusion Language Model Decoding
Trajectory as the Teacher: Few-Step Discrete Flow Matching via Energy-Navigated Distillation
May 8, 2026Amin Karimi Monsefi, Dominic Culver, Nikhil Bhendawade +3Flow Matching Diffusion Language Model Inference
1The Ohio State University · 2Apple

Jun 7, 2026, cs.CLJ/K move · Enter open · S save

AsyncLane: Decoupling Refinement from Advancement in Diffusion Language Model Decoding

Yingxuan Ren, Yuxuan Lou, Yong Liu, Pengcheng Fang+3

1National University of Singapore · University of Southampton

LLM Inference Scheduling Blockwise Diffusion Language Models Diffusion Language Model Inference Diffusion Language Model Decoding Autoregressive Decoding Diffusion Model Inference Acceleration

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Block-wise semi-autoregressive decoding is the standard inference paradigm for diffusion large language models (DLMs), but it imposes a strict dependency between blocks: the next block cannot begin until the current block is fully decoded or its denoising budget is exhausted. We observe that once a block exposes a reliable delimiter boundary or stable semantic prefix, continuation generation need not wait for every residual token to be resolved. We propose AsyncLane, a training-free decoding scheduler that decouples refinement from advancement. AsyncLane forks a generate lane at observed delimiter boundaries into a refine lane and a continuation generate lane: the prefix remains editable, while the continuation advances before prefix refinement finishes. The resulting lane tree records decoding dependencies and output order, while execution proceeds over the active lane set. To make this asynchronous schedule efficient under bidirectional attention, AsyncLane combines shared-prefix lane batching, lookahead draft reuse, cascading termination, and compact cache refresh with refresh-logit reuse, preventing model-call cost from scaling directly with the number of lanes. AsyncLane is a drop-in replacement for block-wise DLM samplers and requires no retraining. Experiments on mathematical reasoning and code generation show that AsyncLane consistently improves throughput while maintaining competitive quality. Across LLaDA and Dream backbones, AsyncLane achieves the highest TPS in all evaluated benchmark-length settings; relative to the fastest competing baseline, it reaches peak speedups of 2.95x on LLaDA and 3.04x on Dream, with especially large gains under longer generation budgets.

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