{"total":814,"rows":[{"id":"2105.05233","title":"Diffusion Models Beat GANs on Image Synthesis","created":"2021-05-11","cited_by_count":8255,"area":"diffusion"},{"id":"2207.12598","title":"Classifier-Free Diffusion Guidance","created":"2022-07-26","cited_by_count":5847,"area":"diffusion"},{"id":"2307.01952","title":"SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis","created":"2023-07-04","cited_by_count":4356,"area":"diffusion"},{"id":"2102.09672","title":"Improved Denoising Diffusion Probabilistic Models","created":"2021-02-18","cited_by_count":3761,"area":"diffusion"},{"id":"2112.10741","title":"GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models","created":"2021-12-20","cited_by_count":3614,"area":"diffusion"},{"id":"2204.03458","title":"Video Diffusion Models","created":"2022-04-07","cited_by_count":2305,"area":"diffusion"},{"id":"2303.01469","title":"Consistency Models","created":"2023-03-02","cited_by_count":1822,"area":"diffusion"},{"id":"2304.08818","title":"Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models","created":"2023-04-18","cited_by_count":1476,"area":"diffusion"},{"id":"2009.09761","title":"DiffWave: A Versatile Diffusion Model for Audio Synthesis","created":"2020-09-21","cited_by_count":1354,"area":"diffusion"},{"id":"2106.15282","title":"Cascaded Diffusion Models for High Fidelity Image Generation","created":"2021-05-30","cited_by_count":1163,"area":"diffusion"},{"id":"2209.04747","title":"Diffusion Models in Vision: A Survey","created":"2022-09-10","cited_by_count":1015,"area":"diffusion"},{"id":"2310.11513","title":"GenEval: An Object-Focused Framework for Evaluating Text-to-Image Alignment","created":"2023-10-17","cited_by_count":972,"area":"diffusion"},{"id":"2308.16512","title":"MVDream: Multi-view Diffusion for 3D Generation","created":"2023-08-31","cited_by_count":938,"area":"diffusion"},{"id":"2301.13188","title":"Extracting Training Data from Diffusion Models","created":"2023-01-30","cited_by_count":732,"area":"diffusion"},{"id":"2210.03142","title":"On Distillation of Guided Diffusion Models","created":"2022-10-06","cited_by_count":725,"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":"2212.08751","title":"Point-E: A System for Generating 3D Point Clouds from Complex Prompts","created":"2022-12-16","cited_by_count":699,"area":"diffusion"},{"id":"2310.05737","title":"Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation","created":"2023-10-09","cited_by_count":640,"area":"diffusion"},{"id":"2112.07804","title":"Tackling the Generative Learning Trilemma with Denoising Diffusion GANs","created":"2021-12-15","cited_by_count":516,"area":"diffusion"},{"id":"2209.12152","title":"All are Worth Words: A ViT Backbone for Diffusion Models","created":"2022-09-25","cited_by_count":502,"area":"diffusion"},{"id":"2401.12945","title":"Lumiere: A Space-Time Diffusion Model for Video Generation","created":"2024-01-23","cited_by_count":455,"area":"diffusion"},{"id":"2210.08933","title":"DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models","created":"2022-10-17","cited_by_count":450,"area":"diffusion"},{"id":"2310.14189","title":"Improved Techniques for Training Consistency Models","created":"2023-10-22","cited_by_count":439,"area":"diffusion"},{"id":"2104.14951","title":"SRDiff: Single Image Super-Resolution with Diffusion Probabilistic Models","created":"2021-04-30","cited_by_count":415,"area":"diffusion"},{"id":"2312.02696","title":"Analyzing and Improving the Training Dynamics of Diffusion Models","created":"2023-12-05","cited_by_count":402,"area":"diffusion"},{"id":"2212.05032","title":"Training-Free Structured Diffusion Guidance for Compositional Text-to-Image Synthesis","created":"2022-12-09","cited_by_count":388,"area":"diffusion"},{"id":"2312.00858","title":"DeepCache: Accelerating Diffusion Models for Free","created":"2023-12-01","cited_by_count":359,"area":"diffusion"},{"id":"2101.02388","title":"Knowledge Distillation in Iterative Generative Models for Improved Sampling Speed","created":"2021-01-07","cited_by_count":348,"area":"diffusion"},{"id":"2304.08466","title":"Synthetic Data from Diffusion Models Improves ImageNet Classification","created":"2023-04-17","cited_by_count":327,"area":"diffusion"},{"id":"2305.08891","title":"Common Diffusion Noise Schedules and Sample Steps are Flawed","created":"2023-05-15","cited_by_count":310,"area":"diffusion"},{"id":"2205.09853","title":"MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and Interpolation","created":"2022-05-19","cited_by_count":309,"area":"diffusion"},{"id":"2312.06662","title":"Photorealistic Video Generation with Diffusion Models","created":"2023-12-11","cited_by_count":306,"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":"2510.11690","title":"Diffusion Transformers with Representation Autoencoders","created":"2025-10-13","cited_by_count":295,"area":"diffusion"},{"id":"2303.14420","title":"Human Preference Score: Better Aligning Text-to-Image Models with Human Preference","created":"2023-03-25","cited_by_count":287,"area":"diffusion"},{"id":"2208.09392","title":"Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise","created":"2022-08-19","cited_by_count":276,"area":"diffusion"},{"id":"2302.04304","title":"Q-Diffusion: Quantizing Diffusion Models","created":"2023-02-08","cited_by_count":273,"area":"diffusion"},{"id":"2303.07909","title":"Text-to-image Diffusion Models in Generative AI: A Survey","created":"2023-03-14","cited_by_count":265,"area":"diffusion"},{"id":"2303.17189","title":"LayoutDiffusion: Controllable Diffusion Model for Layout-to-image Generation","created":"2023-03-30","cited_by_count":259,"area":"diffusion"},{"id":"2312.02201","title":"ImageDream: Image-Prompt Multi-view Diffusion for 3D Generation","created":"2023-12-02","cited_by_count":257,"area":"diffusion"},{"id":"2209.02646","title":"A Survey on Generative Diffusion Model","created":"2022-09-06","cited_by_count":240,"area":"diffusion"},{"id":"2305.18455","title":"Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models","created":"2023-05-29","cited_by_count":236,"area":"diffusion"},{"id":"2504.10483","title":"REPA-E: Unlocking VAE for End-to-End Tuning with Latent Diffusion Transformers","created":"2025-04-14","cited_by_count":225,"area":"diffusion"},{"id":"2105.14080","title":"Gotta Go Fast When Generating Data with Score-Based Models","created":"2021-05-28","cited_by_count":219,"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":"2404.04057","title":"Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation","created":"2024-04-05","cited_by_count":214,"area":"diffusion"},{"id":"2306.04675","title":"Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models","created":"2023-06-07","cited_by_count":205,"area":"diffusion"},{"id":"2212.01206","title":"DiffRF: Rendering-Guided 3D Radiance Field Diffusion","created":"2022-12-02","cited_by_count":204,"area":"diffusion"},{"id":"2212.11972","title":"Scalable Adaptive Computation for Iterative Generation","created":"2022-12-22","cited_by_count":195,"area":"diffusion"},{"id":"2301.10972","title":"On the Importance of Noise Scheduling for Diffusion Models","created":"2023-01-26","cited_by_count":194,"area":"diffusion"},{"id":"2202.05830","title":"Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Quality","created":"2022-02-11","cited_by_count":182,"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":"2406.01125","title":"$\\Delta$-DiT: A Training-Free Acceleration Method Tailored for Diffusion Transformers","created":"2024-06-03","cited_by_count":175,"area":"diffusion"},{"id":"2302.07685","title":"Video Probabilistic Diffusion Models in Projected Latent Space","created":"2023-02-15","cited_by_count":171,"area":"diffusion"},{"id":"2106.00132","title":"On Fast Sampling of Diffusion Probabilistic Models","created":"2021-05-31","cited_by_count":170,"area":"diffusion"},{"id":"2305.10657","title":"PTQD: Accurate Post-Training Quantization for Diffusion Models","created":"2023-05-18","cited_by_count":170,"area":"diffusion"},{"id":"2303.11435","title":"Inversion by Direct Iteration: An Alternative to Denoising Diffusion for Image Restoration","created":"2023-03-20","cited_by_count":165,"area":"diffusion"},{"id":"2302.06588","title":"Raising the Cost of Malicious AI-Powered Image Editing","created":"2023-02-13","cited_by_count":163,"area":"diffusion"},{"id":"2412.10193","title":"Simple Guidance Mechanisms for Discrete Diffusion Models","created":"2024-12-13","cited_by_count":155,"area":"diffusion"},{"id":"2210.00939","title":"Improving Sample Quality of Diffusion Models Using Self-Attention Guidance","created":"2022-10-03","cited_by_count":154,"area":"diffusion"},{"id":"2303.17559","title":"DDP: Diffusion Model for Dense Visual Prediction","created":"2023-03-30","cited_by_count":148,"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":"2312.10240","title":"Rich Human Feedback for Text-to-Image Generation","created":"2023-12-15","cited_by_count":141,"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":"2405.11473","title":"FIFO-Diffusion: Generating Infinite Videos from Text without Training","created":"2024-05-19","cited_by_count":137,"area":"diffusion"},{"id":"2206.07696","title":"Diffusion Models for Video Prediction and Infilling","created":"2022-06-15","cited_by_count":135,"area":"diffusion"},{"id":"2303.07937","title":"Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation","created":"2023-03-14","cited_by_count":133,"area":"diffusion"},{"id":"2310.17347","title":"CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling","created":"2023-10-26","cited_by_count":129,"area":"diffusion"},{"id":"2310.07204","title":"State of the Art on Diffusion Models for Visual Computing","created":"2023-10-11","cited_by_count":127,"area":"diffusion"},{"id":"2312.15821","title":"Audiobox: Unified Audio Generation with Natural Language Prompts","created":"2023-12-25","cited_by_count":120,"area":"diffusion"},{"id":"2304.07060","title":"DCFace: Synthetic Face Generation with Dual Condition Diffusion Model","created":"2023-04-14","cited_by_count":116,"area":"diffusion"},{"id":"2406.08552","title":"DiTFastAttn: Attention Compression for Diffusion Transformer Models","created":"2024-06-12","cited_by_count":115,"area":"diffusion"},{"id":"2309.15214","title":"Residual Corrective Diffusion Modeling for Km-scale Atmospheric Downscaling","created":"2023-09-24","cited_by_count":110,"area":"diffusion"},{"id":"2404.07199","title":"RealmDreamer: Text-Driven 3D Scene Generation with Inpainting and Depth Diffusion","created":"2024-04-10","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":"2412.14167","title":"VideoDPO: Omni-Preference Alignment for Video Diffusion Generation","created":"2024-12-18","cited_by_count":108,"area":"diffusion"},{"id":"2201.00308","title":"DiffuseVAE: Efficient, Controllable and High-Fidelity Generation from Low-Dimensional Latents","created":"2022-01-02","cited_by_count":104,"area":"diffusion"},{"id":"2212.05400","title":"How to Backdoor Diffusion Models?","created":"2022-12-11","cited_by_count":104,"area":"diffusion"},{"id":"2208.14699","title":"Let us Build Bridges: Understanding and Extending Diffusion Generative Models","created":"2022-08-31","cited_by_count":103,"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":"2205.12524","title":"Accelerating Diffusion Models via Early Stop of the Diffusion Process","created":"2022-05-25","cited_by_count":100,"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":"2406.17343","title":"Q-DiT: Accurate Post-Training Quantization for Diffusion Transformers","created":"2024-06-25","cited_by_count":94,"area":"diffusion"},{"id":"2410.01756","title":"ImageFolder: Autoregressive Image Generation with Folded Tokens","created":"2024-10-02","cited_by_count":94,"area":"diffusion"},{"id":"2407.16655","title":"MovieDreamer: Hierarchical Generation for Coherent Long Visual Sequence","created":"2024-07-23","cited_by_count":89,"area":"diffusion"},{"id":"2304.04740","title":"Reflected Diffusion Models","created":"2023-04-10","cited_by_count":87,"area":"diffusion"},{"id":"2302.13861","title":"Differentially Private Diffusion Models Generate Useful Synthetic Images","created":"2023-02-27","cited_by_count":86,"area":"diffusion"},{"id":"2402.12376","title":"FiT: Flexible Vision Transformer for Diffusion Model","created":"2024-02-19","cited_by_count":85,"area":"diffusion"},{"id":"2403.04279","title":"Controllable Generation with Text-to-Image Diffusion Models: A Survey","created":"2024-03-07","cited_by_count":83,"area":"diffusion"},{"id":"2406.04103","title":"Multistep Distillation of Diffusion Models via Moment Matching","created":"2024-06-06","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":"2306.02316","title":"Temporal Dynamic Quantization for Diffusion Models","created":"2023-06-04","cited_by_count":81,"area":"diffusion"},{"id":"2410.07369","title":"An Undetectable Watermark for Generative Image Models","created":"2024-10-09","cited_by_count":81,"area":"diffusion"},{"id":"2305.19693","title":"Spontaneous Symmetry Breaking in Generative Diffusion Models","created":"2023-05-31","cited_by_count":80,"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":"2309.03350","title":"Relay Diffusion: Unifying diffusion process across resolutions for image synthesis","created":"2023-09-04","cited_by_count":79,"area":"diffusion"},{"id":"2405.16005","title":"PTQ4DiT: Post-training Quantization for Diffusion Transformers","created":"2024-05-25","cited_by_count":79,"area":"diffusion"},{"id":"2212.00235","title":"VIDM: Video Implicit Diffusion Models","created":"2022-12-01","cited_by_count":78,"area":"diffusion"},{"id":"2310.03270","title":"EfficientDM: Efficient Quantization-Aware Fine-Tuning of Low-Bit Diffusion Models","created":"2023-10-05","cited_by_count":78,"area":"diffusion"}],"next_cursor":"100"}