{"total":342,"rows":[{"id":"2404.02905","title":"Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction","created":"2024-04-03","cited_by_count":1023,"area":"diffusion"},{"id":"2502.09992","title":"Large Language Diffusion Models","created":"2025-02-14","cited_by_count":912,"area":"diffusion"},{"id":"2310.00426","title":"PixArt-$\\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis","created":"2023-09-30","cited_by_count":864,"area":"diffusion"},{"id":"2410.06940","title":"Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think","created":"2024-10-09","cited_by_count":703,"area":"diffusion"},{"id":"2410.07864","title":"RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation","created":"2024-10-10","cited_by_count":691,"area":"diffusion"},{"id":"2401.03048","title":"Latte: Latent Diffusion Transformer for Video Generation","created":"2024-01-05","cited_by_count":546,"area":"diffusion"},{"id":"2406.03736","title":"Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data","created":"2024-06-06","cited_by_count":381,"area":"diffusion"},{"id":"2303.11305","title":"SVDiff: Compact Parameter Space for Diffusion Fine-Tuning","created":"2023-03-20","cited_by_count":338,"area":"diffusion"},{"id":"2403.04692","title":"PixArt-\\Sigma: Weak-to-Strong Training of Diffusion Transformer for 4K Text-to-Image Generation","created":"2024-03-07","cited_by_count":329,"area":"diffusion"},{"id":"2303.00848","title":"Understanding Diffusion Objectives as the ELBO with Simple Data Augmentation","created":"2023-03-01","cited_by_count":304,"area":"diffusion"},{"id":"2406.02507","title":"Guiding a Diffusion Model with a Bad Version of Itself","created":"2024-06-04","cited_by_count":299,"area":"diffusion"},{"id":"2405.08748","title":"Hunyuan-DiT: A Powerful Multi-Resolution Diffusion Transformer with Fine-Grained Chinese Understanding","created":"2024-05-14","cited_by_count":298,"area":"diffusion"},{"id":"2410.11081","title":"Simplifying, Stabilizing and Scaling Continuous-Time Consistency Models","created":"2024-10-14","cited_by_count":283,"area":"diffusion"},{"id":"2506.15564","title":"Show-o2: Improved Native Unified Multimodal Models","created":"2025-06-18","cited_by_count":250,"area":"diffusion"},{"id":"2303.09556","title":"Efficient Diffusion Training via Min-SNR Weighting Strategy","created":"2023-03-16","cited_by_count":246,"area":"diffusion"},{"id":"2410.10733","title":"Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models","created":"2024-10-14","cited_by_count":217,"area":"diffusion"},{"id":"2602.02214","title":"Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation","created":"2026-02-02","cited_by_count":184,"area":"diffusion"},{"id":"2306.09305","title":"Fast Training of Diffusion Models with Masked Transformers","created":"2023-06-15","cited_by_count":176,"area":"diffusion"},{"id":"2211.13449","title":"Fast Sampling of Diffusion Models via Operator Learning","created":"2022-11-24","cited_by_count":175,"area":"diffusion"},{"id":"2502.06764","title":"History-Guided Video Diffusion","created":"2025-02-10","cited_by_count":171,"area":"diffusion"},{"id":"2411.05007","title":"SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models","created":"2024-11-07","cited_by_count":170,"area":"diffusion"},{"id":"2411.07975","title":"JanusFlow: Harmonizing Autoregression and Rectified Flow for Unified Multimodal Understanding and Generation","created":"2024-11-12","cited_by_count":163,"area":"diffusion"},{"id":"2405.04233","title":"Vidu: a Highly Consistent, Dynamic and Skilled Text-to-Video Generator with Diffusion Models","created":"2024-05-07","cited_by_count":160,"area":"diffusion"},{"id":"2408.06070","title":"ControlNeXt: Powerful and Efficient Control for Image and Video Generation","created":"2024-08-12","cited_by_count":159,"area":"diffusion"},{"id":"2406.01733","title":"Learning-to-Cache: Accelerating Diffusion Transformer via Layer Caching","created":"2024-06-03","cited_by_count":142,"area":"diffusion"},{"id":"2405.05945","title":"Lumina-T2X: Transforming Text into Any Modality, Resolution, and Duration via Flow-based Large Diffusion Transformers","created":"2024-05-09","cited_by_count":137,"area":"diffusion"},{"id":"2406.18583","title":"Lumina-Next: Making Lumina-T2X Stronger and Faster with Next-DiT","created":"2024-06-05","cited_by_count":132,"area":"diffusion"},{"id":"2410.10812","title":"HART: Efficient Visual Generation with Hybrid Autoregressive Transformer","created":"2024-10-14","cited_by_count":132,"area":"diffusion"},{"id":"2401.11605","title":"Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers","created":"2024-01-21","cited_by_count":118,"area":"diffusion"},{"id":"2212.09462","title":"Latent Diffusion for Language Generation","created":"2022-12-19","cited_by_count":115,"area":"diffusion"},{"id":"2406.02540","title":"ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation","created":"2024-06-04","cited_by_count":115,"area":"diffusion"},{"id":"2503.07565","title":"Inductive Moment Matching","created":"2025-03-10","cited_by_count":113,"area":"diffusion"},{"id":"2307.01831","title":"DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation","created":"2023-07-04","cited_by_count":110,"area":"diffusion"},{"id":"2308.09388","title":"Diffusion Models for Image Restoration and Enhancement: A Comprehensive Survey","created":"2023-08-18","cited_by_count":109,"area":"diffusion"},{"id":"2504.05741","title":"DDT: Decoupled Diffusion Transformer","created":"2025-04-08","cited_by_count":109,"area":"diffusion"},{"id":"2507.01467","title":"Representation Entanglement for Generation: Training Diffusion Transformers Is Much Easier Than You Think","created":"2025-07-02","cited_by_count":102,"area":"diffusion"},{"id":"2409.16211","title":"MaskBit: Embedding-free Image Generation via Bit Tokens","created":"2024-09-24","cited_by_count":98,"area":"diffusion"},{"id":"2502.03444","title":"Masked Autoencoders Are Effective Tokenizers for Diffusion Models","created":"2025-02-05","cited_by_count":96,"area":"diffusion"},{"id":"2305.18474","title":"Make-An-Audio 2: Temporal-Enhanced Text-to-Audio Generation","created":"2023-05-29","cited_by_count":90,"area":"diffusion"},{"id":"2506.14603","title":"Align Your Flow: Scaling Continuous-Time Flow Map Distillation","created":"2025-06-17","cited_by_count":87,"area":"diffusion"},{"id":"2402.12376","title":"FiT: Flexible Vision Transformer for Diffusion Model","created":"2024-02-19","cited_by_count":85,"area":"diffusion"},{"id":"2506.05573","title":"PartCrafter: Structured 3D Mesh Generation via Compositional Latent Diffusion Transformers","created":"2025-06-05","cited_by_count":84,"area":"diffusion"},{"id":"2511.20645","title":"PixelDiT: Pixel Diffusion Transformers for Image Generation","created":"2025-11-25","cited_by_count":83,"area":"diffusion"},{"id":"2312.04557","title":"GenTron: Diffusion Transformers for Image and Video Generation","created":"2023-12-07","cited_by_count":82,"area":"diffusion"},{"id":"2507.23268","title":"PixNerd: Pixel Neural Field Diffusion","created":"2025-07-31","cited_by_count":82,"area":"diffusion"},{"id":"2412.15205","title":"FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching","created":"2024-12-19","cited_by_count":80,"area":"diffusion"},{"id":"2311.18257","title":"Diffusion Models Without Attention","created":"2023-11-30","cited_by_count":75,"area":"diffusion"},{"id":"2410.19324","title":"Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion","created":"2024-10-25","cited_by_count":75,"area":"diffusion"},{"id":"2504.02436","title":"SkyReels-A2: Compose Anything in Video Diffusion Transformers","created":"2025-04-03","cited_by_count":73,"area":"diffusion"},{"id":"2405.14224","title":"DiM: Diffusion Mamba for Efficient High-Resolution Image Synthesis","created":"2024-05-23","cited_by_count":72,"area":"diffusion"},{"id":"2312.11417","title":"PolyDiff: Generating 3D Polygonal Meshes with Diffusion Models","created":"2023-12-18","cited_by_count":66,"area":"diffusion"},{"id":"2407.11633","title":"Scaling Diffusion Transformers to 16 Billion Parameters","created":"2024-07-16","cited_by_count":66,"area":"diffusion"},{"id":"2502.15894","title":"RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers","created":"2025-02-21","cited_by_count":66,"area":"diffusion"},{"id":"2410.10356","title":"FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification","created":"2024-10-14","cited_by_count":64,"area":"diffusion"},{"id":"2410.03456","title":"Dynamic Diffusion Transformer","created":"2024-10-04","cited_by_count":62,"area":"diffusion"},{"id":"2405.17405","title":"Human4DiT: 360-degree Human Video Generation with 4D Diffusion Transformer","created":"2024-05-27","cited_by_count":61,"area":"diffusion"},{"id":"2306.04542","title":"On the Design Fundamentals of Diffusion Models: A Survey","created":"2023-06-07","cited_by_count":60,"area":"diffusion"},{"id":"2412.03859","title":"CreatiLayout: Siamese Multimodal Diffusion Transformer for Creative Layout-to-Image Generation","created":"2024-12-05","cited_by_count":60,"area":"diffusion"},{"id":"2511.19365","title":"DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation","created":"2025-11-24","cited_by_count":60,"area":"diffusion"},{"id":"2503.14445","title":"Bolt3D: Generating 3D Scenes in Seconds","created":"2025-03-18","cited_by_count":59,"area":"diffusion"},{"id":"2405.18428","title":"DiG: Scalable and Efficient Diffusion Models with Gated Linear Attention","created":"2024-05-28","cited_by_count":56,"area":"diffusion"},{"id":"2410.08261","title":"Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis","created":"2024-10-10","cited_by_count":56,"area":"diffusion"},{"id":"2411.01738","title":"xDiT: an Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism","created":"2024-11-04","cited_by_count":56,"area":"diffusion"},{"id":"2505.02831","title":"No Other Representation Component Is Needed: Diffusion Transformers Can Provide Representation Guidance by Themselves","created":"2025-05-05","cited_by_count":56,"area":"diffusion"},{"id":"2403.17870","title":"Boosting Diffusion Models with Moving Average Sampling in Frequency Domain","created":"2024-03-26","cited_by_count":55,"area":"diffusion"},{"id":"2405.02730","title":"U-DiTs: Downsample Tokens in U-Shaped Diffusion Transformers","created":"2024-05-04","cited_by_count":54,"area":"diffusion"},{"id":"2407.00783","title":"Diffusion Models and Representation Learning: A Survey","created":"2024-06-30","cited_by_count":54,"area":"diffusion"},{"id":"2403.17004","title":"SD-DiT: Unleashing the Power of Self-supervised Discrimination in Diffusion Transformer","created":"2024-03-25","cited_by_count":49,"area":"diffusion"},{"id":"2405.15330","title":"Towards Understanding the Working Mechanism of Text-to-Image Diffusion Model","created":"2024-05-24","cited_by_count":48,"area":"diffusion"},{"id":"2410.14919","title":"Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step","created":"2024-10-19","cited_by_count":47,"area":"diffusion"},{"id":"2508.00413","title":"DC-AE 1.5: Accelerating Diffusion Model Convergence with Structured Latent Space","created":"2025-08-01","cited_by_count":47,"area":"diffusion"},{"id":"2402.05608","title":"Scalable Diffusion Models with State Space Backbone","created":"2024-02-08","cited_by_count":45,"area":"diffusion"},{"id":"2404.04095","title":"Dynamic Prompt Optimizing for Text-to-Image Generation","created":"2024-04-05","cited_by_count":45,"area":"diffusion"},{"id":"2412.01199","title":"TinyFusion: Diffusion Transformers Learned Shallow","created":"2024-12-02","cited_by_count":45,"area":"diffusion"},{"id":"2412.07720","title":"ACDiT: Interpolating Autoregressive Conditional Modeling and Diffusion Transformer","created":"2024-12-10","cited_by_count":45,"area":"diffusion"},{"id":"2504.16064","title":"Boosting Generative Image Modeling via Joint Image-Feature Synthesis","created":"2025-04-22","cited_by_count":45,"area":"diffusion"},{"id":"2507.23523","title":"H-RDT: Human Manipulation Enhanced Bimanual Robotic Manipulation","created":"2025-07-31","cited_by_count":45,"area":"diffusion"},{"id":"2410.08184","title":"Scaling Laws For Diffusion Transformers","created":"2024-10-10","cited_by_count":44,"area":"diffusion"},{"id":"2409.02097","title":"LinFusion: 1 GPU, 1 Minute, 16K Image","created":"2024-09-03","cited_by_count":43,"area":"diffusion"},{"id":"2411.09943","title":"Zero-shot Voice Conversion with Diffusion Transformers","created":"2024-11-15","cited_by_count":43,"area":"diffusion"},{"id":"2311.16567","title":"MobileDiffusion: Instant Text-to-Image Generation on Mobile Devices","created":"2023-11-28","cited_by_count":42,"area":"diffusion"},{"id":"2404.04478","title":"Diffusion-RWKV: Scaling RWKV-Like Architectures for Diffusion Models","created":"2024-04-06","cited_by_count":41,"area":"diffusion"},{"id":"2407.03297","title":"Improved Noise Schedule for Diffusion Training","created":"2024-07-03","cited_by_count":39,"area":"diffusion"},{"id":"2412.12444","title":"LazyDiT: Lazy Learning for the Acceleration of Diffusion Transformers","created":"2024-12-17","cited_by_count":37,"area":"diffusion"},{"id":"2505.16792","title":"REPA Works Until It Doesn't: Early-Stopped, Holistic Alignment Supercharges Diffusion Training","created":"2025-05-22","cited_by_count":37,"area":"diffusion"},{"id":"2404.02883","title":"On the Scalability of Diffusion-based Text-to-Image Generation","created":"2024-04-03","cited_by_count":36,"area":"diffusion"},{"id":"2406.09416","title":"Alleviating Distortion in Image Generation via Multi-Resolution Diffusion Models and Time-Dependent Layer Normalization","created":"2024-06-13","cited_by_count":36,"area":"diffusion"},{"id":"2505.19114","title":"CreatiDesign: A Unified Multi-Conditional Diffusion Transformer for Creative Graphic Design","created":"2025-05-25","cited_by_count":36,"area":"diffusion"},{"id":"2310.11142","title":"BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference","created":"2023-10-17","cited_by_count":35,"area":"diffusion"},{"id":"2502.06805","title":"Efficient Diffusion Models: A Survey","created":"2025-02-03","cited_by_count":35,"area":"diffusion"},{"id":"2412.15032","title":"DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space","created":"2024-12-19","cited_by_count":34,"area":"diffusion"},{"id":"2509.04394","title":"Transition Models: Rethinking the Generative Learning Objective","created":"2025-09-04","cited_by_count":34,"area":"diffusion"},{"id":"2402.14167","title":"T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching","created":"2024-02-21","cited_by_count":33,"area":"diffusion"},{"id":"2502.12154","title":"Diffusion Models without Classifier-free Guidance","created":"2025-02-17","cited_by_count":33,"area":"diffusion"},{"id":"2406.11427","title":"DiTTo-TTS: Diffusion Transformers for Scalable Text-to-Speech without Domain-Specific Factors","created":"2024-06-17","cited_by_count":32,"area":"diffusion"},{"id":"2503.18414","title":"U-REPA: Aligning Diffusion U-Nets to ViTs","created":"2025-03-24","cited_by_count":32,"area":"diffusion"},{"id":"2403.09176","title":"Switch Diffusion Transformer: Synergizing Denoising Tasks with Sparse Mixture-of-Experts","created":"2024-03-14","cited_by_count":31,"area":"diffusion"},{"id":"2409.10819","title":"EzAudio: Enhancing Text-to-Audio Generation with Efficient Diffusion Transformer","created":"2024-09-17","cited_by_count":31,"area":"diffusion"},{"id":"2411.16725","title":"$\\textit{Revelio}$: Interpreting and leveraging semantic information in diffusion models","created":"2024-11-23","cited_by_count":30,"area":"diffusion"},{"id":"2409.19365","title":"Conditional Image Synthesis with Diffusion Models: A Survey","created":"2024-09-28","cited_by_count":29,"area":"diffusion"}],"next_cursor":"100"}