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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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lenient 5/5
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71%Highly rated
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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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76%Highly rated
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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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80%Must read
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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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76%Highly rated
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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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57%Worth a look
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NeurIPS 2026Shanghai JiaotongDiffusion models

A Favorable Regime Between ODE and SDE for Few-Step Diffusion Sampling

YIhao Bu, Dan Lian, Zhenguo Gao

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

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57%Worth a look
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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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67%Highly rated
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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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45%Niche pick
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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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67%Highly rated
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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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