Diffusion Transformer

Also known as DiT

Diffusion Transformers (DiTs) use transformer networks to turn noise into data, typically by repeatedly predicting denoising updates or following a learned flow. Work explores latent- and pixel-space models, conditioning through text, images, geometry, or other modalities, and representation-learning methods that improve generation and downstream perception. To lower the cost of training and inference, researchers use sparse attention, token reduction, caching, quantization, distillation, and hardware-aware designs. A central challenge is balancing speed, memory, and model size against fidelity, temporal or spatial consistency, and reliable performance across tasks and benchmarks.

Latest papers

473 papers78 papers in the last four weeks, up 100% on the four weeks before. 0.5% of all new papers.

SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers
May 21, 2026Javad Rajabi, Kimia Shaban, Koorosh Roohi +2Rotary Positional Embeddings Diffusion Model Guidance
University of Toronto · Vector Institute
ORBIS: Output-Guided Token Reduction with Distribution-Aware Matching for Video Diffusion Acceleration
May 21, 2026Hangyeol Lee, Joo-Young KimToken Merging Video Diffusion Models
KAIST · Daejeon, South Korea
Rethinking Token Reduction for Diffusion Models via Output-Similarity-Awareness
May 21, 2026Hangyeol Lee, Hyojeong Lee, Joo-Young KimDiffusion Transformer Diffusion-Based Image Generation
KAIST, Daejeon, Republic of Korea
RiT: Vanilla Diffusion Transformers Suffice in Representation Space
May 21, 2026Le Zhang, Ning Mang, Aishwarya AgrawalFlow Matching Visual Representation Learning
Mila – Québec AI Institute, UdeM · Utrecht University · Canada CIFAR AI Chair
Instrumental Text-to-Music Generation with Auxiliary Conditioning Branches
May 20, 2026Junyoung KohText-to-Music Generation Diffusion Transformer
Department of Artificial Intelligence, Yonsei University MAAP KRAFTON Seoul, Republic of Korea
OcclusionFormer: Arranging Z-Order for Layout-Grounded Image Generation
May 20, 2026Ziye Li, Henghui DingDiffusion Transformer Occlusion Reasoning
Institute of Big Data, College of Computer Science and Artificial Intelligence, Fudan University, China.
Rethinking Cross-Layer Information Routing in Diffusion Transformers
May 20, 2026Chao Xu, Maohua Li, Qirui Li +9Diffusion Transformer Residual Learning
Alibaba Group · Nanjing University · Zhejiang University +1
RoPeSLR: 3D RoPE-driven Sparse-LowRank Attention for Efficient Diffusion Transformers
May 20, 2026Yuxi Liu, Zekun Zhang, Yixiang Cai +3Rotary Positional Embeddings Low-Rank Attention
Peking University · University of Electronic Science and Technology of China · Beijing University of Posts and Telecommunications
Pareto-Enhanced Portrait Generation: Vision-Aligned Text Supervision for Alignment, Realism, and Aesthetics
May 20, 2026Yunlong Wang, Jinjin Shi, Wenbin Gao +3Diffusion Model Alignment Diffusion Transformer
Xiaomi Corporation Nanjing, China · Xiaomi Corporation Beijing, China
Improved Baselines with Representation Autoencoders
May 18, 2026Jaskirat Singh, Boyang Zheng, Zongze Wu +3Diffusion Model Guidance Diffusion Transformer
Adobe Research · ANU · New York University
Learning to Balance: Decoupled Siamese Diffusion Transformer for Reference-Based Remote Sensing Image Super-Resolution
May 18, 2026Bin Luo, Runmin Dong, Zhaoyang Luo +4Diffusion Models for Image Restoration Diffusion Transformer
Tsinghua Shenzhen International Graduate School, Shenzhen, China · Sun Yat-sen University, Zhuhai, China · Tsinghua University, Beijing, China +1
AdaptiveLoad: Towards Efficient Video Diffusion Transformer Training
May 18, 2026Yucheng Guo, Yongjian Guo, Zhong Guan +6Video Diffusion Models GPU Kernel Optimization
JD AI Infra, Beijing, China · Tsinghua University, Beijing, China
HierEdit: Region-Aware Hierarchical Diffusion for Efficient High-Resolution Editing
May 17, 2026Yuyao Zhang, Alexander Huang-Menders, Yu-Wing TaiDiffusion Transformer Diffusion-Based Image Editing
Dartmouth College
Beyond Point-Wise Matching: Structural Representation Alignment for Accelerating Diffusion Transformers
May 16, 2026Shaodong Xu, Zhendong Wang, Litong Gong +4Diffusion Model Alignment Diffusion Transformer
University of Science and Technology of China
DiRotQ: Rotation-Aware Quantization for 4-bit Diffusion Transformers
May 16, 2026Sayeh Sharify, Mahsa Salmani, Hesham MostafaDiffusion Transformer Diffusion Model Quantization
d-Matrix Santa Clara, CA 95054
Registers Matter for Pixel-Space Diffusion Transformers
May 15, 2026Nikita Starodubcev, Ilia Sudakov, Ilya Drobyshevskiy +2Diffusion Transformer Diffusion Guidance
Yandex Research
HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion
May 15, 2026Yu He, Lichen Ma, Zipeng Guo +5Diffusion Transformer Image Generation
ElasticDiT: Efficient Diffusion Transformers via Elastic Architecture and Sparse Attention for High-Resolution Image Generation on Mobile Devices
May 15, 2026Kunpeng Du, Haizhen Xie, Sen Lu +11Diffusion Transformer Diffusion-Based Image Generation
Huawei Technologies
DreamSR: Towards Ultra-High-Resolution Image Super-Resolution via a Receptive-Field Enhanced Diffusion Transformer
May 15, 2026Qingji Dong, Hang Dong, Mingqin Chen +2Diffusion Models for Image Restoration Diffusion Model Guidance
ByteDance Inc.
DealMaTe: Multi-Dimensional Material Transfer via Diffusion Transformer
May 15, 2026Nisha Huang, Yizhou Lin, Jie Guo +3Diffusion Transformer Diffusion-Based Image Editing
Tsinghua University, China · Pengcheng Laboratory, China · National Cheng-Kung University, Taiwan +2
MaTe: Images Are All You Need for Material Transfer via Diffusion Transformer
May 15, 2026Nisha Huang, Henglin Liu, Yizhou Lin +5Diffusion Transformer Diffusion-Based Image Editing
Tsinghua University · PengCheng Laboratory · Lenovo Research +1
Self-Prompting Diffusion Transformer for Open-Vocabulary Scene Text Editing via In-Context Learning
May 15, 2026Hongxi Li, Tong Wang, Chengjing Wu +6Diffusion Transformer Text-Guided Image Editing
1MT Lab, Meitu Inc., Beijing, China · School of Computer Science & Technology, Beijing Institute of Technology, Beijing, China
SEDiT: Mask-Free Video Subtitle Erasure via One-step Diffusion Transformer
May 14, 2026Zheng Hui, Yunlong BaiDiffusion Transformer Video Editing
Baidu Inc., Beijing, China.
HASTE: Training-Free Video Diffusion Acceleration via Head-Wise Adaptive Sparse Attention
May 14, 2026Xuzhe Zheng, Yuexiao Ma, Jing Xu +3Video Diffusion Models Diffusion Transformer
1Key Laboratory of Multimedia Trusted Perception and Efficient Computing, Ministry of Education of China, Xiamen University, 361005, P.R. China
Head Forcing: Long Autoregressive Video Generation via Head Heterogeneity
May 14, 2026Jiahao Tian, Yiwei Wang, Gang Yu +1Diffusion Transformer Autoregressive Diffusion
AGI Lab, Westlake University · University of California at Merced · StepFun
Diagnosing and Correcting Concept Omission in Multimodal Diffusion Transformers
May 14, 2026Kanghyun Baek, Jaihyun Lew, Chaehun Shin +2Diffusion Transformer T2I Generation
Interdisciplinary Program in Artificial Intelligence, Seoul National University, Seoul, South Korea · Department of Electrical and Computer Engineering, Seoul National University, Seoul, South Korea · Department of Computer Science & Engineering, Korea University, Seoul, South Korea +1
CoReDiT: Spatial Coherence-Guided Token Pruning and Reconstruction for Efficient Diffusion Transformers
May 13, 2026Zhuojin Li, Hsin-Pai Cheng, Hong Cai +2Diffusion Transformer Visual Token Pruning
Qualcomm AI Research†
TeDiO: Temporal Diagonal Optimization for Training-Free Coherent Video Diffusion
May 13, 2026Nurislam Tursynbek, Zhiqiang Lao, Heather Yu +2Video Diffusion Models Diffusion Transformer
UNC Chapel Hill1 · Futurewei Technologies Inc2 · UCSD3
Few Channels Draw The Whole Picture: Revealing Massive Activations in Diffusion Transformers
May 13, 2026Evelyn Turri, Davide Bucciarelli, Sara Sarto +2Diffusion Transformer Massive Activations
University of Modena and Reggio Emilia, Italy · University of Pisa, Italy
OP4KSR: One-Step Patch-Free 4K Super-Resolution with Periodic Artifact Suppression
May 13, 2026Chengyan Deng, Pengbin Yu, Zhentao Chen +6Diffusion Transformer Diffusion Model Inference Acceleration
School of Automation Engineering, University of Electronic Science and Technology of China · OPPO AI Center, OPPO Inc. · School of Intelligence Science and Technology, Nanjing University

May 21, 2026J/K move · Enter open · S save

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

Javad Rajabi, Kimia Shaban, Koorosh Roohi, David B. Lindell+1

University of Toronto · Vector Institute

Rotary Positional Embeddings Diffusion Model Guidance Diffusion Transformer Position Extrapolation T2I Diffusion Models

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Diffusion transformers (DiTs) have emerged as a dominant architecture for text-to-image generation, yet their performance drops when generating at resolutions beyond their training range. Existing training-free approaches mitigate this by modifying inference-time attention behavior, often through Rotary Position Embeddings (RoPE) extrapolation combined with attention scaling. However, these strategies apply a uniform and content-agnostic scaling across RoPE components with distinct frequency characteristics, inducing a trade-off between preserving global structure and recovering fine detail. We introduce SEGA, a training-free method that dynamically scales attention across RoPE components according to the latent's spatial-frequency structure at each denoising step. This adaptive scaling improves both structural coherence and fine-detail fidelity. Experiments show that SEGA consistently improves high-resolution synthesis across multiple target resolutions, outperforming state-of-the-art training-free baselines.