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arXivDiffusion models

LiFT: Loop Flow Transformers

Loop Flow Transformers loop a shared diffusion transformer with depth-indexed regression targets, improving generation with more inference compute and fewer parameters than dense models.

Mohammad Mahdi Derakhshani, Pedro M. P. Curvo, Gertjan J. Burghouts, Jan-Willem van de Meent and 1 more

Published Oct 4, 2026 · ▲ 9 on Hugging Face

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arXivDiffusion models

COSMI: COmpositional Synthesis of Multi-object Interactions

COSMI synthesizes multi-object interactions by composing local single-object clips, yielding a 222k-sequence dataset and a diffusion model that generalizes to unseen object-interaction pairs with higher contact accuracy.

Daniel Eskandar, Ilya A. Petrov, Gerard Pons‐Moll

Published Oct 2, 2026 · 0 citations · ▲ 7 on Hugging Face · Code ★ 8

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arXivDiffusion models

DMAD: Distribution Matching as Adversarial Distillation for Fast Visual Generation

DMAD recasts distribution matching as adversarial distillation with discriminator heads to eliminate auxiliary score models, achieving state-of-the-art few-step image, video, and audio-video generation.

Zhengming Yu, 袁俊坤, Haotian Yang, Gordon Guocheng Qian and 7 more

Published Oct 1, 2026 · 0 citations · ▲ 3 on Hugging Face · Code

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arXivDiffusion models

SALD: Self-Referenced Advantage Learning for Diffusion Models

SALD self-references diffusion training via dual noise-level error differences and spectral residuals to improve generation without teachers or extra parameters.

Aryan Das, Surjo Dey, Koushik Biswas, Swalpa Kumar Roy and 3 more

Published Oct 1, 2026 · 0 citations

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arXivHefei University of TechnologyTsinghuaZhipu AIDiffusion models

GFD-OPD: Guidance-Folded On-Policy Distillation of Diffusion Models Across Scales

GFD-OPD fixes diffusion on-policy distillation by reducing student-teacher gaps and preventing classifier-free guidance error amplification, achieving state-of-the-art compression results.

Zhenxing Zhang, Jiayan Teng, Wenxu Wu, Zhuoyi Yang and 5 more

Published Sep 30, 2026 · 0 citations

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arXivDiffusion models

UniMate: One Unified Model to Animate Diverse Skeletons

UniMate is a unified diffusion transformer that synthesizes motion for arbitrary skeletons from text and rigged assets without test-time optimization, using topology-aware attention and a new dataset to outperform specialized animators.

Linzhan Mou, Lei, Jiahui, Zhiyang Dou, Chenyue Cai and 3 more

Published Sep 4, 2026 · 0 citations · ▲ 23 on Hugging Face · Code ★ 1,553

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arXivDiffusion models

Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer

Z-Image is a 6B-parameter diffusion image generator that achieves leading open-source performance with only 314K GPU hours, sub-second inference, and consumer-hardware compatibility.

Image Team, Cai, Huanqia, Cao, Sihan, Du, Ruoyi and 20 more

Published Nov 27, 2025 · 1 citation · ▲ 249 on Hugging Face · Code ★ 12,067

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NeurIPS 2026Westlake University / ZhejiangAlibaba GroupZhejiang University, TsinghuaSoutheastWestlakeDiffusion models

SpaG-DiT: Enhancing Spatial Grounding for Diffusion Transformers

Zongliang Wu, Benlei Cui, Longtao Huang, Xiaoqian Xia and 5 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Warsaw, Centre for CredibleMassachusetts General Hospital, Warsaw University of TechnologyCentre for Credible AIMassachusetts General Hospital， Diffusion models

Local Intrinsic Dimension Unveils Hallucinations in Diffusion Models

Bartlomiej Sobieski, Matthew Tivnan, Dawid Płudowski, Michał J Włodarczyk and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U British ColumbiaU CambridgeDiffusion models

PDE-SSM: A Spectral State Space Approach to Spatial Mixing in Diffusion Transformers

Eshed Gal, Moshe Eliasof, Eldad Haber

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U PennsylvaniaPrincetonFAIR, MetaDiffusion models

Do Diffusion Models Learn to Generalize Basic Visual Skills?

Amish Sethi, Boya Zeng, Wenhao Chai, Zhuang Liu

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The University of QueenslandELLIS Institute Finland | AaltoTU MunichAaltoDiffusion models

Directional Noise Conditioning for Diffusion Models

Mahdi Shafiei, Azade Farshad, Nassir Navab, Yousef Yeganeh

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026DGISTDaegu Gyeongbuk Institute of SciDiffusion models

RB-LDC: Redundancy-Balanced Latent Coding for Robust Diffusion

Hyunseok Jeong, Jaeho Jeon, Young-Sik Kim

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026InhaDiffusion models

Tethered Predictive-Inertial Proposals with Objective Verification for Diffusion-Prior Inverse Problems

Minwoo Kim, Seunghyeok Shin, Dabin Kim, Hongki Lim

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U ChicagoZhejiangWestlakeDiffusion models

Quantifying and Optimizing Path Uncertainty in Masked Diffusion Models

Ziyu Chen, Xinbei Jiang, PENG SUN, Tao Lin

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SJTUNankaiAlibaba GroupBeihangShanghai JiaotongDiffusion models

What Matters for Diffusion-Friendly Latent Manifold? Prior-Aligned Autoencoders for Latent Diffusion

Zhengrong Yue, Taihang Hu, Mengting Chen, Haiyu Zhang and 7 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026KAISTKorea Advanced Institute of ScieMila - Quebec Artificial IntelliU EdinburghUniversité de Montréal & MilDiffusion models

Aligning Few-Step Generative Model via Amortizing Sample-Based Variational Inference

Jaewoo Lee, Hyeongyu Kang, Dohyun Kim, Kyuil Sim and 8 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026CREST, ENSAEKing's College London, UnivGENES-CREST/ENSAEDiffusion models

Stein Transport for Generative Modeling

Clémentine CHAZAL, Linfeng Wang, Anna Korba, Nikolas Nüsken

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Tsinghua Shenzhen International ShandongTsinghuaHarbin Institute of Technology, Pengcheng LaboratoryDiffusion models

From Generation to Restoration: Residual Diffusion for Neural Channel Decoding

Qinshan Zhang, Shipeng Guo, Xuantai Wu, Bin Chen and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Hefei University of TechnologyDiffusion models

Disentangling Dual Image References in Frequency Aware Diffusion Models for Personalized Generation

Haipeng Liu, Yang Wang, Meng Wang

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Massachusetts Institute of TechnUT AustinMITDiffusion models

Self-Cleaning Diffusion Models

Adrian Rodriguez-Munoz, Adam Klivans, Antonio Torralba, Constantinos Daskalakis and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Nanyang TechnologicalXidianNanyang Technological UniversityDiffusion models

PRISM: Human Point Cloud Reconstruction via Skeleton-Guided Diffusion from MmWave Radar

Jiacheng Huang, Long Tian, Yuan Liu, Andy Khong

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Nanjing University of Science anNankaiNanjing University / RIKENNanjingDiffusion models

Beyond Generation: Unlocking Discriminative Representations from Diffusion Models

Haowen Cui, Ge Wu, Shuo Chen, Yikai Ge and 4 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026LY CorporationLY Corp.Diffusion models

Where and When Identity Forms: Identity-Vital Attention Redistribution for Training-Free Subject-Driven Generation

Luan Thanh Trinh, Atsuki Osanai, Kenji Doi

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightIntelligent Science & TechnoBaiduChina Aerospace Science and InduBeijing University of AeronauticPekingDiffusion models

All-Addition Spiking Diffusion Models with Attention Enhancement

Yuhan Zhang, Yuanpei Chen, Zhou Jie, Weihang Peng and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The Hong Kong PolytechnicHong Kong PolytechnicThe Hong Kong Polytechnic UnivDiffusion models

Phase-wise Velocity Distillation: Towards Effective Image Generation with A Single NFE

Zhen Guo, Rongyuan Wu, Qiaosi Yi, Chenxi Xie and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Korea Advanced Institute of ScieKorea Advanced Institute of ScieKAISTDiffusion models

SchedDiff: Diffusion-Based Priority Refinement for Job Shop Scheduling

Dong-Yoon Oh, Sang-Hyun Cho, Inguk Choi, Hyun-Jung Kim

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SUN YAT-SEN UNIVERSITYU the Chinese Academy of ScienceShenzhen Campus of Sun Yat-senHuawei Technologies Ltd.Diffusion models

Beyond Single-Shot Conditioning: Test-Time Condition Refinement for Diffusion-Based Image Restoration

Aiping Zhang, Jiangang Wang, Shangquan Sun, Yuning Cui and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Samsung AI Center-TorontoSamsung AI CentreSamsung AI Centre TorontoSamsungAI Center Toronto, Samsung ElectDiffusion models

HalluciText: Mitigating Text Hallucinations in Diffusion-Based Image Restoration

Zhiming Hu, Angela Ye, Ran Zhang, Tristan T Aumentado-Armstrong and 6 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026nanjing universityAustralian NationalNanyang TechnologicalNational University of SingaporeNanjingDiffusion models

Beyond the Dirac Delta: Mitigating Diversity Collapse in Reinforcement Fine-Tuning for Image Generation

Jinmei Liu, Haoru Li, Zhenhong Sun, Chaofeng Chen and 5 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026XIDIAN UNIVERSITYXidianHangzhou Institute of TechnologyU Technology SydneyDiffusion models

StyleRoute: Diffusion Style Transfer via Regional Routing and Conflict-aware Projection

Xunhao Lin, Yu Sun, Xinpeng Ding, Fei Gao and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Indian Institute of Technology DIndian Institute of Technology (Diffusion models

ManifoldCache: Training-Free Diffusion Acceleration via Constraint Manifold Caching

Prashant Pandey, Sri Venkatraya Chowdary Devineni, Brejesh Lall

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Technische Universität MünchenBMW AGTechnical University of MunichDiffusion models

CRISP: Fixing Flying Pixels in Latent LiDAR Generation via Diffusion Decoding

Andrea Ceron, Michael Schmidt, Alvaro Marcos-Ramiro, Sebastian Schmidt and 1 more

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Nanyang TechnologicalYonseiKorea Advanced Institute of ScieDiffusion models

Systematic Hazard Sampling: Minimal-Variance Inference for Discrete Diffusion and Flow Models

Seunghwan Jang, Wonje Jeung, SooJean Han

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The Chinese University of Hong KThe Hong Kong University of ScieChinese University of Hong KongTechnical University of MunichDepartment of Computer Science aDiffusion models

DiffCool: Label-Free Synthesis of Chip-Tailored Heat Sinks via Thermal-Aware Diffusion

Siyuan Liang, Zixiao Wang, Chenghan Wang, Shanyi Li and 6 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U California, BerkeleyFudanCOWAROBOTSouth ChinaShanghai Jiao TongDiffusion models

Do We Really Need Diffusion for Generative Object Detection? A Minimal Prototype Perspective

Yu Hong, Xiaosong Jia, Yihan Wang, Wenlong Liao and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Shanghai JiaotongSouthern University of Science aAlibaba GroupInstitute of Artificial IntelligThe Hong Kong University of ScieDiffusion models

Z-Cache: Accelerating Diffusion Transformers via Self-Reflection

Zegang Cheng, Zhikai Wang, Jiacheng Liu, Xiaobing Tu and 7 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightKing's College LondonKing's College London, UnivDiffusion models

Improving the Diffusability of Motion Tokenizer

Guanhe Huang, Songqiao Han, Tangzheng Lian, Oya Celiktutan

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Shanghai JiaotongKing's College LondonINRIADiffusion models

LITHE: Lattice-Indexed Twin Hadamard Encoding for Diffusion Personalization

Jian Jiang, Oya Celiktutan, Yaohui WANG, Yutong Ban

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SUN YAT-SEN UNIVERSITYAlibaba GroupKey Laboratory of Intelligent InU Chinese Academy of SciencesDiffusion models

Why DiT Models Underperform as Representation Learners without Long Skip Connections

Benyuan Meng, Yiliang Zhang, Jin-Wen Wu, Qianqian Xu and 2 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Shanghai Jiao Tongvivo Mobile Communication Co., LShanghai JiaotongAlibaba GroupU AlbertaDiffusion models

Opening the Black Box of Classifier-Free Guidance via Information Bottleneck

Jiayang Gao, Tianyi Zheng, Jiayang Zou, Fengxiang Yang and 4 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Alibaba GroupNanjingZhejiangCity University of Hong KongU RochesterDiffusion models

Rethinking Cross-Layer Information Routing in Diffusion Transformer

Chao Xu, Maohua Li, Qirui Li, Yixuan Xu and 8 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026TongjiDiffusion models

UniDBO: A Unified Dual-Branch One-Step Denoising Framework for Autonomous Driving Scenario Generation

Da Zhao, Yuhang Chen, Jie Sun, Jialin Fan and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026TsinghuaKuaishouMeituanPengcheng LaboratoryDiffusion models

Efficient Hybrid Distillation: Synergizing Score and Adversarial Objectives for One-Step Diffusion

Fei Peng, Junqiang Wu, Haoxian Tan, Jun Zhou and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026School of Robotics, WuhanWuhanSoutheastDiffusion models

CoVisIT: Cross-modal Prior Guided Diffusion Model for Visible-to-Infrared Image Translation

Linfeng Tang, Tong Hu, Zizhuo Li, Hao Zhang and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026PekingXiamenTsinghua University, TsinghuaPeng Cheng LaboratoryDiffusion models

Tikhonov-Stabilized Bezier Representation Forecasting for Training-free Diffusion Acceleration

Lei Zhu, Mujie Lin, Ruochong Zheng, Guangyi Wang and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Carnegie MellonU PittsburghDiffusion models

Discrete Diffusion Playground: A 2D Benchmark for Discrete Generative Models

Justin Shao, Sihyun Park, David Koes, Maria Chikina

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U the Chinese Academy of ScienceZhejiangAlibaba GroupMeituanDiffusion models

Masked Generative Pretraining Improves Cross-Dataset Transfer in Pixel-Space Diffusion

Shu Wei, Jiachen Lei, Jiahong Wu, Xiangxiang Chu

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U UtahU Wisconsin-MadisonNational TaiwanDiffusion models

Test-Time Sequential Steering of Diffusion Models via Preconditioned Crank-Nicolson

Joel Keller, Taos Transue, Qin Li, Shih-Hsin Wang and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026National University of Defense TDiffusion models

PISG: Constraint-Aligned Signal Amplification for Diffusion-Based Combinatorial Optimization

Yuming Zhang, Xianchen Zhou, Hongxia Wang

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SoutheastMonashDiffusion models

IRCasDiff: Two-Stage Cascaded Diffusion for Compound Infrared Face Reconstruction

Zhiyuan Xia, Haojie Li, Yiguo Qiao, Cunjian Chen

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Xi'an JiaotongNanjingDiffusion models

Rethinking Diffusion Decoding via Structural Commitment

Lipeng Wan, Anbang Wang, Zixuan Yang, Kun Xu and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026CornellDiffusion models

Unsupervised Concept Discovery with Dirichlet Concept Diffusion Models

Yuchong Geng, Ao Tang

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Xi'an Jiaotong University &JD.comJD RetailDiffusion models

FrequencyBooster: Advancing Pixel Diffusion for High-Fidelity Image Generation

Lichen Ma, Zipeng Guo, Yu He, Xiaolong Fu and 4 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U OxfordVGG, University of OxfordNanyang TechnologicalMeta and University of OxfordDiffusion models

Track4D: Representing Dense 3D Tracking for Video Diffusion Models

Yushi LAN, Zeren Jiang, Kelvin Zheng Li, Xingang Pan and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026RIKENKarlsruher Institut für TechnoloZuse Institute Berlindida, Zuse Institute BerlinDiffusion models

A Trust Region Approach for Learning Schrödinger Bridges

Takeshi Koshizuka, Denis Blessing, Max Zimmer, Sebastian Pokutta and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026StanfordDiffusion models

Order-Marginalized Scoring for Masked Diffusion Models

Arthur Deng, Sebastian Thrun

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The University of TokyoRIKEN / University of TokyoDiffusion models

Asymptotically Exact Negative Guidance of Diffusion Models via Positive-Unlabeled Learning

Hirohane Takagi, Masashi Sugiyama

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SogangDonggukDiffusion models

The Quiet Prompt: Erasing Ineffable Styles from Diffusion Models via Concept Leakage-aware Negative Guidance

Kiyun Park, Min Hee Cha, Hyeok Nam, Jae Hyeon Park and 4 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U MichiganU Michigan - Ann ArborThe University of MichiganMichigan StateDiffusion models

Improving Conditional Modeling via Inter-Class Likelihood-Ratio Maximization and Unifying Classifier-Free Guidance with Alignment Objectives

Xiang Li, Yixuan Jia, Xiao Li, Jeffrey Fessler and 2 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Université Paris-SaclayUniversité Paris Dauphine - PSLUniversity Paris-SaclayDiffusion models

Euclidean Score-Based Generative Modeling with Permutation Semantics

Gaël Heck, Nassim Bourarach, Sylvie Le Hégarat-Mascle, Nicolas Lermé

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U Massachusetts BostonNortheasternDiffusion models

Decompose the Distillation: Interpretable Single-Pass Guidance for Diffusion Models

Wuyang Zhang, Xiaolin Xu

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026QualComm AI ResearchQualcommDiffusion models

UltraFlash: Accelerating Megapixel Visual Synthesis

Phuc Lai, Anh Nguyen, Phong H Nguyen, Anh Tran

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Central SouthDiffusion models

Enhanced convergence guarantees of score-based generative models in $\mathcal{W}_2$-distance beyond log-concavity

Zhang Xiaoyan, Chenxu Pang, Xiaojie Wang

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026POSTECHDiffusion models

Analyzing Learning-Dynamics Across Loss and Prediction Choices for Diffusion Models

Dongwoo Kim

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026NankaiAlibaba GroupAnt GroupRenmin University of ChinaDiffusion models

Diffusion Transformers with Residual Adaptive Layer Normalization

Ge Wu, Minxing Luo, Yikai Ge, Lei Wang and 7 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Seoul NationalKorea Advanced Institute of ScieKookminDiffusion models

ManiFusion: Unlocking High-Throughput Generation via Superposition in Manifold Space

Minkyu Kim, Baekseung Kim, Junhoo Lee, Jangho Kim and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Pusan NationalDiffusion models

Mixture-of-Hierarchical Experts: Optimized Mamba Architecture for Vision Diffusion

Yejun Jung, Dongyun Kim, Jinsun Park

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Illinois at Urbana-ChampaignU Illinois, Urbana ChampaignUIUCDiffusion models

VASR: Variance-Aware Systematic Resampling for Diffusion Models

Shivanshu Shekhar, Sagnik Mukherjee, Jia Y Zhang, Tong Zhang

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026The Chinese University of Hong KWestlakeCUHK-ShenzhenDiffusion models

DrPO: Drifting Preference Optimization for One-Step Generative Models

Zhou Jiang, Yandong Wen, Zhen Liu

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026State University of New York at Stony BrookArgonne National LaboratoryAcademic medical center at StateU UtahDiffusion models

BigCell: Generating Gigapixel Whole-Slide Images

Srikar Yellapragada, Alexandros Graikos, Zilinghan Li, Kostas Triaridis and 9 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Johns HopkinsJohns Hopkins UnivU Massachusetts at AmherstJohns Hopkins MedicineVanderbiltDiffusion models

Magnetic Resonance Unpaired Image Translation with Pseudometric Schrödinger Bridges

Shuwen Wei, Samuel Remedios, Zhangxing Bian, Shimeng Wang and 8 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026YonseiSeoul NationalDiffusion models

From Static Geometry to Dynamical Singularity: Detecting Memorization in Diffusion Models via Score Evolution

Jeonseong Kim, Chenglin Fan

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Hong Kong PolytechnicColumbiaDiffusion models

ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Scheduling

Yilie Huang, Wenpin Tang, XUNYU ZHOU

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026POSTECHChung-AngDiffusion models

ProxySearch: Decoupled Inference-Time Scaling for Diffusion Models via Asymmetric Noise-Rank Transfer

Seungwook Kim, Jongmin Lee

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026King Abdullah University of ScieNorthwesternDiffusion models

D-DOIT: Training-free Adaptation of Discrete Diffusion via Doob's h-Transform

Jieke Wu, Qijie Zhu, Weimin Wu, Zeqi Ye and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026OaklandNorth Carolina StateDiffusion models

Geometry-Aware Score-Repellent Monte Carlo

Jie Hu, Lingyun Chen, Do-Young Eun

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Ocean University of ChinaSan Diego StateDiffusion models

EGCA: A Spectral Perspective on Forward Process Design in Diffusion Models

Chi Zhang, Guichao Chang, Sirui Liu, Xin Zhang and 1 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026KAISTKAIST, Korea Advanced Institute Korea Advanced Institute of ScieDiffusion models

Improving Guidance-Free Visual Generation via Self-Contrastive Alignment for Likelihood Estimation

Jiwan Hur, DongJae Lee, Dongyeun Lee, Gyojin Han and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U California, Los AngelesNVIDIANVIDIA ResearchDiffusion models

SCULPT: Advancing Masked Discrete Diffusion for High-Resolution Image Synthesis.

Shufan Li, Greg Heinrich, Hanrong Ye, Yonggan Fu and 3 more

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026peking universityXi'an JiaotongWestlakeU Southern CaliforniaShanghai JiaotongDiffusion models

Not All Slots Are Equal: Non-Co-Progressive Markov Bridge for Bundle Construction

Rongchao Zhang, Haodong Jing, Siheng Wang, Zhengtao Yao and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026TsinghuaDiffusion models

BridgeTwist: Twisting Schrödinger Bridges for Training-Free Conditional Sampling

Mengyu Li, Qianqian Qu, Jun Liu

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightThe Hong Kong University of ScieAdobe ResearchHong Kong University of Science Adobe SystemsThe Hong Kong University of ScieDiffusion models

UltraDiff:Transferring High-Fidelity Priors to Compressed Latent Spaces for High-resolution Image Generation

Jingjing Ren, Haitian Zheng, Haoyu Chen, Connelly Barnes and 4 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026SoutheastU Science and Technology BeijingWuhanDiffusion models

V2VFusion: Text-Controlled Video-to-Video Diffusion for Degradation-Aware Video Fusion

Jiajun Chen, Han Xu, Yunfei Huang, Zhuoya Zhang and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026, TsinghuaTsinghuaTsinghua University, TsinghuaTsinghuaDiffusion models

Co-GRPO: Co-Optimized Group Relative Policy Optimization for Masked Image Generation

Renping Zhou, Zanlin Ni, Tianyi Chen, Zeyu Liu and 5 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The University of Tokyo; RIKEN AMBZUAIRIKENMohamed bin Zayed University of RIKEN / University of TokyoDiffusion models

DELTA: Robustly Training Label-Conditional Diffusion Models with Weak Annotations

Dong-Dong Wu, Jiacheng Cui, Wei Wang, Zhiqiang Shen and 1 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Singapore ManagementDiffusion models

Per-Starting-Point Plausibility and Diversity Bounds for Score-Based Diffusion Models

Minh Quang Nguyen, Hady Lauw

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026CornellTogether AICornell University / ASAPP ReseaDiffusion models

Empowering Masked Diffusion Models to Self-Correct with Leave-One-Out Transformers

Sofian Zalouk, Vincent Counathe, Paul Jünger, Daniel Cao and 3 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026The Chinese University of Hong KU SydneyTsinghua Shenzhen International Shanghai AI LabDiffusion models

VUM: Visual Unified Models for Image Generation and Perception

ZiDong Wang, Yiyuan Zhang, Xiaoyu Yue, Xiangyuan Xue and 3 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SiChuanSichuanDiffusion models

FADE: Fractional Anomalous Dynamics Extrapolation for Training-Free Diffusion Transformers Acceleration

Jinlong Yang, Jinke Wu, Lizilin, Yao Zhou

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026KAISTKAIST AIKorea Advanced Institute of ScieDiffusion models

DualDrift: Combining Forward and Reverse Drifts for One-Step Generative Modeling

Hojung Jung, Juhyeong Kim, Jaehyun Kwak, Boryeong Cho and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026HanyangHanyang UniverstyDiffusion models

Which Tokens to Merge? Diffusion Dynamics for Efficient Image Generation

SeungJu Cha, Ye-Chan Kim, HyunGee Kim, Sungho Koh and 1 more

Atlanta Poster Session 5, Fri, Dec 11, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026TulaneDiffusion models

Where to Look Is Not How to Fix: Pre-Denoising Diagnostics and Modality-Dependent Control in Diffusion Composition

Fangzheng Wu, Brian Summa

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U Science and Technology of ChinAlibaba GroupNortheasternDiffusion models

MaskSense: Confronting the Visual Exploration Trap in Masked Image Generation

Yawen Shao, Jie Xiao, Kai Zhu, Yu Liu and 5 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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76%Highly rated
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NeurIPS 2026DukeDiffusion models

Multilevel and Sequential Monte Carlo for Training-Free Diffusion Guidance

A sequential Monte Carlo framework with multilevel variance reduction provides unbiased diffusion guidance, achieving state-of-the-art training-free conditional generation with lower cost.

Aidan Gleich, Scott C Schmidler

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026Imperial College LondonDiffusion models

Steering Optimisation Trajectories in Diffusion Representation Learning

Diffusion autoencoders learn different latent structures via distinct optimization regimes, and SteeringDRL steers training toward disentanglement by targeting U-Net shortcuts and using a noise-level curriculum.

Rajat Rasal, Tian Xia, Avinash Kori, Ben Glocker

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026UC BerkeleyGoogle Deepmind / HarvardDiffusion models

Equilibrium Matching: Generative Modeling with Implicit Energy-Based Models

Equilibrium Matching learns implicit energy landscapes for optimization-based sampling, surpassing diffusion models with 1.90 FID on ImageNet 256x256 while supporting denoising, OOD detection, and composition.

Runqian (Ray) Wang, Yilun Du

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 7 on Hugging Face · Code ★ 217

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NeurIPS 2026U TorontoHarvardMicrosoft Research New EnglandCMU, Carnegie MellonU LjubljanaDiffusion models

Test-time Scaling of Diffusions with Flow Maps

Flow Map Trajectory Tilting uses flow maps to enable principled diffusion test-time scaling with reward gradients, improving reward ascent and enabling complex image editing via vision-language models.

Amirmojtaba Sabour, Michael Albergo, Carles Domingo i Enrich, Nicholas Boffi and 3 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 6 on Hugging Face

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NeurIPS 2026Massachusetts Institute of TechnMITDiffusion models

Specificity-Aware Diffusion Steering via Variance-Reduced Sequential Monte Carlo

Specificity-aware diffusion steering uses variance-reduced sequential Monte Carlo to suppress undesired regions with minimal positive distribution distortion.

Luran Wang, Linrui Ma, Hannes Stark, Regina Barzilay

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026NankaiAlibaba GroupSJTUAlibaba Inc.Diffusion models

Continuous-Time Distribution Matching for Few-Step Diffusion Distillation

Continuous-Time Distribution Matching replaces discrete step anchoring with continuous distribution optimization and off-trajectory alignment to accelerate diffusion models without auxiliary networks. CDM achieves competitive few-step image generation fidelity across architectures without GANs or re

Tao Liu, Hao Yan, Mengting Chen, Taihang Hu and 7 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026 · ▲ 27 on Hugging Face · Code ★ 154

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NeurIPS 2026U California, San DiegoU California San DiegoUC San DiegoUCSDDiffusion models

Distance Marching for Generative Modeling

Distance Marching improves time-unconditional generative models via distance-focused losses and inference, surpassing flow matching FID with fewer steps and aiding OOD detection.

Zimo Wang, Ishit Mehta, Haolin Lu, Xunpeng Huang and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026GoogleDiffusion models

The Geometry of Noise: Why Diffusion Models Don't Need Noise Conditioning

Autonomous diffusion models implicitly optimize a marginal energy landscape via Riemannian gradient flow, where a learned conformal metric neutralizes geometric singularities near data; velocity parameterization ensures stability, but noise prediction fails via a Jensen gap.

Mojtaba Sahraee-Ardakan, Mauricio Delbracio, Peyman Milanfar

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightMassachusetts Institute of TechnMITDiffusion models

The Value of Covariance Matching in Gaussian DDPMs and the Lanczos Sampler

Matching full posterior covariance in Gaussian DDPMs reduces path-KL error to O(1/T²), and the matrix-free Lanczos Gaussian sampler achieves this with exponentially decaying approximation error using only Jacobian-vector products.

Sahil Akhtar, Aymane El Gadarri, Vivek Farias, Adam Jozefiak

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Imperial College LondonU PotsdamDiffusion models

Diffusion Path Samplers via Sequential Monte Carlo

Diffusion-based samplers use sequential Monte Carlo along diffusion paths to estimate scores and densities, with control variates reducing variance across OU, interpolant, and annealed paths.

James Matthew Young, Paula Cordero-Encinar, Sebastian Reich, Andrew Duncan and 1 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U AmsterdamSurfSARAGoogle DeepmindGoogle BrainGoogle DeepMindDiffusion models

Dual-Rate Diffusion: Accelerating diffusion models with an interleaved heavy-light network

Dual-Rate Diffusion accelerates diffusion inference by interleaving sparse heavy context encoders with light denoising models, cutting computation 2-4x without quality loss.

Grigory Bartosh, David Ruhe, Emiel Hoogeboom, Jonathan Heek and 2 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026École PolytechniqueINRIAInria Paris / ENSMohamed bin Zayed University of CMU/MBZUAI/GenBioDiffusion models

Uniform Diffusion Models revisited: Leave-One-Out Denoiser and Absorbing State Reformulation

Standard uniform diffusion training uses a leave-one-out posterior rather than the true denoising posterior, causing a parameterization-objective mismatch that new conversions, samplers, and an absorbing-state reformulation fix to match masked diffusion.

Samson Gourevitch, Yazid Janati, Dario Shariatian, Umut Simsekli and 3 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026 · ▲ 4 on Hugging Face · Code ★ 11

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NeurIPS 2026KAISTDiffusion models

LENS: Low-Frequency Eigen Noise Shaping for Efficient Diffusion Sampling

LENS modulates low-frequency noise subspaces via a lightweight network to boost distilled diffusion quality, cutting compute and parameters by orders of magnitude versus prior methods.

Haewon Jeon, Si-Hyeon Lee

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Spotlightnanjing universityTencent Youtu LabTencent YouTu LabYoutu Lab, TencentNanjingDiffusion models

L2P: Unlocking Latent Potential for Pixel Generation

L2P transfers pre-trained latent diffusion models to pixel space via frozen intermediate layers and synthetic data, enabling efficient 4K generation with near-source performance.

Zhennan Chen, Junwei Zhu, Xu Chen, Jiangning Zhang and 6 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 36 on Hugging Face · Code ★ 195

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NeurIPS 2026U Virginia, CharlottesvilleU VirginiaDARPA; University of Colorado BoDiffusion models

Search-Augmented Masked Diffusion Models for Constrained Generation

SearchDiff integrates informed search into masked diffusion denoising to enforce hard constraints and optimize non-differentiable properties at inference time without retraining, outperforming discrete diffusion and autoregressive baselines.

Huu Binh Ta, Michael Cardei, Alvaro Velasquez, Ferdinando Fioretto

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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78%Highly rated
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NeurIPS 2026NorthwesternNorthwestern University, NorthweU MichiganDiffusion models

DiffATS: Diffusion in Aligned Tensor Space

DiffATS uses orthogonal Procrustes-aligned Tucker primitives to enable direct diffusion modeling of high-resolution spatiotemporal fields, achieving 3.9x to 210x compression without pretrained autoencoders.

Jinhua Lyu, Tianmin Yu, Brian Kim, Lizhuo Zhou and 2 more

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026The University of Hong KongThe Chinese University of Hong KWuhanHuazhong University of Science aDiffusion models

EO-WM: A Physically Informed World Model for Probabilistic Earth Observation Forecasting

EO-WM is a diffusion transformer that forecasts satellite imagery via physically structured weather conditioning and improves vegetation-decline prediction accuracy by up to 7.8% on new diagnostic benchmarks.

Junwei Luo, Shuai Yuan, Zhenya YANG, Yansheng Li and 2 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 3 on Hugging Face · Code ★ 33

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NeurIPS 2026Ho Chi Minh city University of SHo Chi Minh city University of SU North Carolina at CharlotteDiffusion models

Learning to Generate Multiple Objects from Dense and Occluded Layouts

Layout-aware attention biases and amodal-balanced loss prevent instance ownership collapse, substantially improving object count accuracy in dense, occluded scenes.

Bach H Ngo, Ngo Tri, Hieu Le, Trung Nghia Le

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ZhejiangFudanJD Explore AcademyDiffusion models

DecQ: Detail-Condensing Queries for Enhanced Reconstruction and Generation in Representation Autoencoders

DecQ uses lightweight detail-condensing queries to extract fine-grained VFM features, improving representation autoencoder reconstruction and generative fidelity without disrupting semantic space.

Tianhang Wang, Yitong Chen, Wei Song, Zuxuan Wu and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 3 on Hugging Face · Code ★ 8

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NeurIPS 2026Duke UnversityDuke University, DukeDukeDiffusion models

Variational Trajectory Optimization of Anisotropic Diffusion Schedules

A variational framework learns matrix-valued anisotropic diffusion schedules and improves EDM across CIFAR-10, AFHQv2, FFHQ, and ImageNet-64.

Pengxi Liu, Zeyu M Li, Xiang Cheng

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026U Cambridge Google DeepMindUniversity Of TrentoU CambridgeSAPDiffusion models

Tabular Foundation Model for Generative Modelling

TabFORGE introduces a tabular generative foundation model using causality-aware representations and two-stage diffusion-decoder training to generate high-fidelity synthetic data.

Xiangjian Jiang, Mingxuan Liu, Nikola Simidjievski, Tassilo Klein and 1 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026KAISTGeorgia Institute of TechnologyDiffusion models

Coarse-to-Fine Compositional Diffusion for Long-Horizon Planning

CoFi separates global structure formation from local refinement via coarse scaffolds, improving long-horizon compositional diffusion coherence with 2-8x fewer denoiser evaluations.

Byoungwoo Park, Utkarsh Mishra, Jaemoo Choi, Juho Lee and 1 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026PekingTiktokSingapore University of TechnoloBytedance, USDiffusion models

DC-SAE: Deep Compression Semantic Autoencoder for Faster Diffusion Convergence

DC-SAE combines semantic and pixel-level encoders to achieve 32x compression with high fidelity and faster diffusion convergence. It achieves 29.79 PSNR and 3.37 gFID on ImageNet 512x512, outperforming prior high-compression tokenizers by large margins.

Xu Huang, Ye Huang, Zijun Liao, Yuwei Niu and 5 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 42 on Hugging Face · Code ★ 18

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71%Highly rated
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NeurIPS 2026U OxfordInria Paris / ENSU CopenhagenDiffusion models

Metropolis-Adjusted Diffusion Models

Metropolis-adjusted Langevin correctors using score-based acceptance probabilities and a two-coin Bernoulli factory reduce diffusion model sampling bias and improve FID.

Kevin H. Lam, Tyler Farghly, Christopher Williams, Jun Yang and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Virginia Polytechnic Institute aMetaVirginia TechDiffusion models

ReGDiff: Guided Diffusion in Regulated Latent Space for Exploring Metamaterial Voxel Geometry

ReGDiff couples regulated latent diffusion with repel-and-sink smoothing and short-range repulsion guidance to generate plausible, novel metamaterial voxel geometries, improving plausibility by 8.9%, novelty by 46.4%, and diversity by 128.6% over baselines.

Wangzhi Zhan, Jianpeng Chen, Dongqi Fu, Dawei Zhou

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U VirginiaU Virginia, CharlottesvilleMichigan StateMICHIGAN STATE UNIVERSITYAdobe ResearchDiffusion models

PixelDense: Dense Prediction as Representation Alignment for Pixel Diffusion

PixelDense aligns pixel diffusion with frozen dense-prediction teachers via separate semantic and geometric projection streams and orthogonality penalties, improving GenEval to 0.8093 and training speed by 1.23x.

Lehan Yang, Daiqing Qi, Wenhao Zhang, Avery Li and 8 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 20 on Hugging Face · Code ★ 3

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NeurIPS 2026New YorkDiffusion models

Seeking the Unfamiliar but Memorable: Conceptual Creativity as Meta-Learning

Creativity frames a frozen diffusion model as a Creator and an adaptive observer as an Appraiser, using meta-learning gradients to generate novel, quickly learnable concepts.

Mengye Ren

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026OralHebrew University of JerusalemDiffusion models

Colored Noise Diffusion Sampling

Colored Noise Sampling replaces uniform noise with dynamic frequency-dependent schedules to exploit diffusion spectral bias, substantially reducing FID across architectures as a training-free plug-in.

Hadar Davidson, Noam Issachar, Sagie Benaim

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026 · ▲ 19 on Hugging Face · Code ★ 45

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NeurIPS 2026U Illinois Urbana-ChampaignU Illinois at Urbana-ChampaignDiffusion models

Discrete Langevin-Inspired Posterior Sampling

ΔLPS proposes a discrete gradient-informed posterior sampler that enables parallel updates without continuous relaxations, outperforming discrete diffusion samplers and matching continuous solvers across inverse problems.

Sattwik Basu, Chaitanya Amballa, Jorge V Sampedro, Romit Roy Choudhury

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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72%Highly rated
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NeurIPS 2026TsinghuaMicrosoft Research AsiaKlingAIDepartment of Computer Science, Diffusion models

Diffusion Models without Classifier-free Guidance

Model-guidance replaces classifier-free guidance by training on condition posterior probabilities, doubling inference speed and achieving 1.34 FID on ImageNet 256.

Zhicong Tang, Dong Chen, Jianmin Bao, Baining Guo

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 8 on Hugging Face · Code ★ 175

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NeurIPS 2026SpotlightTélécom ParisCEASorbonne Université - Faculté deDiffusion models

Diff-CA: Separating Common and Salient Factors with Diffusion Models

Diff-CA conditions diffusion models to decompose image representations into common and salient factors via weak supervision, achieving high-fidelity contrastive generation and editing with provable factorization identifiability.

Michaël Soumm, Alexandre Fournier Montgieux, Yunlong HE, Pietro Gori and 1 more

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026HKUSTHong Kong University of Science VNET GroupThe Hong Kong University of ScieZhejiangDiffusion models

AHPA: Adaptive Hierarchical Prior Alignment for Diffusion Transformers

AHPA adaptively selects hierarchical VAE feature priors via a timestep-conditioned router to match diffusion transformer alignment granularity to denoising needs, improving convergence without inference overhead.

Ruibin Min, Yexin Liu, Aimin PAN, Changsheng Lu and 4 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026KAISTKorea Advanced Institute of ScieNVIDIADiffusion models

Contrastive Distribution Matching for Amortized Sequential Monte Carlo in Discrete Diffusion

CDM amortizes twisted SMC for discrete diffusion by learning a twist function via contrastive samples, adding under 5% overhead while outperforming baselines on text, DNA, protein, and LLM tasks.

Jaihoon Kim, Taehoon Yoon, Prin Phunyaphibarn, Seungjun Kim and 2 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SpotlightU CambridgeDiffusion models

Recursively Trained Diffusion Models: Limiting Collapse Distribution and Spectral Characterization

Recursive diffusion training converges geometrically to a unique Gaussian-smoothed mixture limit via early-stopping drift, attenuating high-order spectral modes, with annealed truncation schedules asymptotically preventing collapse.

Nail B Khelifa, Richard Turner, Ramji Venkataramanan

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026U TorontoNVIDIANational University of SingaporeU LjubljanaVeeda AIDiffusion models

PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion

PiD reformulates latent decoding as conditional pixel diffusion to synthesize high-resolution images with low latency and high fidelity. It decodes 512×512 latents to 2048×2048 pixels in under one second on consumer GPUs.

Yifan Lu, Qi Wu, Jay Zhangjie Wu, Zian Wang and 3 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 45 on Hugging Face

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NeurIPS 2026U TorontoU TorontoDepartment of Computer Science, Toronto Rehab / University of ToDiffusion models

SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers

SEGA adaptively scales diffusion-transformer attention by latent frequency to improve high-resolution synthesis without training.

Javad Rajabi, Kimia Shaban, Koorosh Roohi, David Lindell and 1 more

Paris Poster Session 2, Wed, Dec 9, 5:00 PM–7:00 PM, Paris Poster Hall · Published 2026 · ▲ 43 on Hugging Face · Code ★ 74

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NeurIPS 2026Nanyang TechnologicalDiffusion models

Training-Free Generative Sampling via Moment-Matched Score Smoothing

MM-SOLD uses moment-matched score smoothing for training-free sampling, matching data moments with diffusion-level fidelity via interacting particles.

ZHENYU YAO, Daniel Paulin

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Australian NationalNew YorkAdobe ResearchAdobeAdobe Research, USDiffusion models

Improved Baselines with Representation Autoencoders

Using summed last-k encoder layers and combining RAE with REPA, RAEv2 achieves state-of-the-art gFID of 1.06 in 80 epochs with 10x faster convergence and free guidance.

Jaskirat Singh, Boyang Zheng, Zongze Wu, Richard Zhang and 2 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026the University of Hong KongU Hong KongDiffusion models

On the Memorization of Consistency Distillation for Diffusion Models

Consistency distillation reduces memorization in diffusion students versus teachers while preserving sample quality by suppressing unstable memorization-linked features and keeping generalizable modes.

Bingqing Jiang, Difan Zou

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Advanced Micro DevicesAMDDiffusion models

DC-DiT: Adaptive Compute and Elastic Inference for Visual Generation via Dynamic Chunking

DC-DiT uses dynamic chunking to adaptively allocate tokens by region and timestep, reducing ImageNet inference FLOPs by up to 36.8% and improving FID by up to 37.8%. Its router enables elastic inference from a single checkpoint with smooth quality-compute tradeoffs.

Akash Haridas, Utkarsh Saxena, Parsa Ashrafi Fashi, Mehdi Rezagholizadeh and 2 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026 · ▲ 16 on Hugging Face

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NeurIPS 2026TsinghuaTsinghua University, TsinghuaStableAISoutheastSiemens Corporate ResearchDiffusion models

Breaking the Quality–Privacy Tradeoff in Tabular Data Generation via In-Context Learning

DiffICL frames tabular synthesis as in-context learning using pretrained structural priors to avoid memorization, improving both quality and privacy in small-data settings.

Xinyan Han, yan Lu, Xiaoyu Lin, Yuanyuan Jiang and 4 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026ETH Zurich, GoogleKoreaGoogleETHZ - ETH ZurichU CopenhagenDiffusion models

Stitched Value Model for Diffusion Alignment

StitchVM stitches pretrained pixel-space reward models onto frozen diffusion backbones to build accurate noisy-latent value functions for efficient diffusion alignment, accelerating DPS 3.2× and DiffusionNFT 2.3×.

Hyojun Go, Hyungjin Chung, Prune Truong, Goutam Bhat and 7 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026 · ▲ 10 on Hugging Face

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NeurIPS 2026The Scripps Research InstituteDiffusion models

GeoSPRINT: Geometric Redundancy-Aware Step Pruning for Inference in Diffusion Trajectories

GeoSPRINT uses trajectory hyperplanarity tests to build non-uniform diffusion sampling schedules that improve FID over uniform DDIM without retraining.

Arpita Joshi

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Beijing University of Post and TBeijing University of Posts and Diffusion models

Structure-Semantic Co-optimized Latent Diffusion Model for Fast Visual Anagram Synthesis

S2CO-Anagram applies structure-semantic co-optimization to adversarially distilled latent diffusion for faster, higher-resolution visual anagrams with improved visual harmony and semantic fidelity.

Xiang Gao, Yunpeng Jia

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026OralU Texas at AustinThe University of Texas at AustiDiffusion models

Query Lower Bounds for Diffusion Sampling

Diffusion sampling requires $\tilde\Omega(\sqrt{d})$ adaptive score queries for $d$-dimensional distributions with polynomial accuracy, proving multiscale schedules are necessary.

Zhiyang Xun, Eric Price

Atlanta Poster Session 4, Thu, Dec 10, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026MBZUAIMohamed bin Zayed University of Pinscreen/University of SouthernDiffusion models

Efficient Image Synthesis with Sphere Latent Encoder

Decoupling sphere encoding into a fixed pretrained encoder and separate spherical latent denoiser improves few-step image generation efficiency and quality.

Tung Do, Thuan H Nguyen, Hao Li

Paris Poster Session 6, Fri, Dec 11, 2:30 PM–4:30 PM, Paris Poster Hall · Published 2026 · ▲ 7 on Hugging Face

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NeurIPS 2026PekingMassachusetts Institute of TechnDiffusion models

FlashMol: High-Quality Molecule Generation in as Few as Four Steps

FlashMol uses distribution-matching distillation and timestep respacing to generate high-quality 3D molecular conformations in as few as four steps, achieving up to 250x speedup over teachers.

Xinyuan Wei, Zian Li, Shaoheng Yan, Cai Zhou and 1 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026UPenn / AppleApple Inc.U Illinois at Urbana-ChampaignAppleDiffusion models

Normalizing Trajectory Models

Normalizing Trajectory Models train expressive conditional normalizing flows for coarse diffusion steps with exact trajectory likelihood, enabling high-quality four-step text-to-image generation.

Jiatao Gu, Tianrong Chen, Ying Shen, David Berthelot and 2 more

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026 · ▲ 13 on Hugging Face

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NeurIPS 2026HarvardU OxfordDiffusion models

Itô maps for any-step SDEs

The paper introduces Itô maps as any-step stochastic flow maps for SDEs that enable efficient single-pass future state prediction, posterior sampling, and inference-time control.

Zhengkai Pan, Peter Potaptchik, Wenxi Yao, Michael Albergo and 1 more

Paris Poster Session 3, Thu, Dec 10, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026PekingTrinity College, DublinNanyang Technologicalnanjing universityIntel Labs ChinaDiffusion models

SteerVTE: Seamless Video Text Editing with Style and Glyph Control

SteerVTE steers frozen video diffusion via style and glyph control for precise, temporally coherent video text editing, outperforming baselines.

Kai Zeng, Moran Li, Zhengwei Wang, Yingchen Yu and 5 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Texas A&MTexas A&MDiffusion models

Inference-Time Search Using Side Information for Diffusion-Based Image Reconstruction

A training-free inference-time search framework incorporates side information into diffusion-based inverse problem solvers to consistently improve reconstruction quality across diverse tasks.

Mahdi Farahbakhsh, Vishnu Teja Kunde, Dileep Kalathil, Krishna Narayanan and 1 more

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Indian Institute of Technology, Department of Electrical EngineeDiffusion models

CAB: Accelerating Flow and Diffusion Sampling via Rectification and Corrected Adams-Bashforth

CAB is a training-free sampler using rectified dynamics and a corrected multistep Adams-Bashforth predictor that achieves third-order local accuracy and improves quality-NFE trade-offs at 6, 20 steps across flow and diffusion models.

Anuska Roy, Pravin Ramachandran Nair

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026U HelsinkiU CambridgeCMU, Carnegie MellonU EdinburghCarnegie MellonDiffusion models

Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences

Spatiotemporal Noise-Contrastive Estimation learns energy-based models via joint spatiotemporal differences to avoid failure modes of spatial or temporal methods alone, matching state-of-the-art density estimation.

Hanlin Yu, RuiKang OuYang, Partha Kaushik, Arto Klami and 2 more

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026SISSAUniversité Paris Dauphine - PSLRadboud University NijmegenBocconiDiffusion models

Emergence of Distortions in High-Dimensional Guided Diffusion Models

Classifier-free guidance induces mismatched sampling distributions in diffusion models, with high-dimensional Gaussian distortions emerging when class counts scale exponentially with dimension, and a negative-guidance schedule improves diversity and separability.

Enrico Ventura, Beatrice Achilli, Luca Ambrogioni, Carlo Lucibello

Paris Poster Session 1, Wed, Dec 9, 12:30 PM–2:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026The Hong Kong University of Scieknowin.aiThe Hong Kong Univeristy of ScieThe Chinese University of Hong KDiffusion models

DirectUV: Image-Conditioned UV Texture Generation with Surface-Aware Positional Encoding

DirectUV generates UV textures via diffusion with surface-aware positional encoding that attains 3D coherence across seams and improves occluded regions.

Jiantao Lin, Yingjie Xu, Mingzhi Sheng, Yangkai Wei and 2 more

Sydney Poster Session 6, Thu, Dec 10, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026University College LondonDiffusion models

Tokenizer-Generator Coupling in Medical Image Generation

Latent medical image generator rankings depend jointly on tokenizer, generator, and sampler choices, with retuned samplers reducing FID to 0.09 and reconstruction PSNR failing as a selection criterion.

Liam Chalcroft

Paris Poster Session 5, Fri, Dec 11, 11:30 AM–1:30 PM, Paris Poster Hall · Published 2026

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NeurIPS 2026LunarAI LLCTempleDiffusion models

Robust Diffusion Models via Divergence-Induced Weighted Denoising

Replacing diffusion denoising loss with f-divergence-induced weights improves contamination robustness via bounded-influence residual downweighting, cutting CIFAR-10 FID from 93.0 to 77.5 under 30% contamination.

Lei Li, Yuexiao Dong

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Chalmers University of TechnologChalmers University of TechnologSISSABocconiChalmers/GUDiffusion models

The Interplay of Data Structure and Imbalance in the Learning Dynamics of Diffusion Models

Diffusion models learn high-variance classes first, but sampling imbalance can reverse this ordering and delay minority class learning, causing uneven memorization.

Flavio Nicoletti, Chenxiao Ma, Enrico Ventura, Luca Saglietti and 1 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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ICML 2026WorkshopKorea Advanced Institute of ScieKAISTKAIST AIDiffusion models

Reward Score Matching: Unifying Reward-based Fine-tuning for Flow and Diffusion Models

Reward Score Matching unifies reward-based diffusion and flow fine-tuning via value-guided score matching, clarifying tradeoffs and yielding simpler, more efficient designs.

Jeongjae Lee, Jinho Chang, Jeongsol Kim, Jong Chul Ye

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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