{"total":135,"rows":[{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863,"area":"diffusion"},{"id":"2102.09672","title":"Improved Denoising Diffusion Probabilistic Models","created":"2021-02-18","cited_by_count":3761,"area":"diffusion"},{"id":"2111.05826","title":"Palette: Image-to-Image Diffusion Models","created":"2021-11-10","cited_by_count":1300,"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":"2006.09011","title":"Improved Techniques for Training Score-Based Generative Models","created":"2020-06-16","cited_by_count":1043,"area":"diffusion"},{"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":"2209.04747","title":"Diffusion Models in Vision: A Survey","created":"2022-09-10","cited_by_count":1015,"area":"diffusion"},{"id":"2407.01392","title":"Diffusion Forcing: Next-token Prediction Meets Full-Sequence Diffusion","created":"2024-07-01","cited_by_count":681,"area":"diffusion"},{"id":"2101.09258","title":"Maximum Likelihood Training of Score-Based Diffusion Models","created":"2021-01-22","cited_by_count":672,"area":"diffusion"},{"id":"2108.02938","title":"ILVR: Conditioning Method for Denoising Diffusion Probabilistic Models","created":"2021-08-06","cited_by_count":635,"area":"diffusion"},{"id":"2406.04329","title":"Simplified and Generalized Masked Diffusion for Discrete Data","created":"2024-06-06","cited_by_count":626,"area":"diffusion"},{"id":"2111.15640","title":"Diffusion Autoencoders: Toward a Meaningful and Decodable Representation","created":"2021-11-30","cited_by_count":449,"area":"diffusion"},{"id":"2208.04202","title":"Analog Bits: Generating Discrete Data using Diffusion Models with Self-Conditioning","created":"2022-08-08","cited_by_count":373,"area":"diffusion"},{"id":"2101.12072","title":"Autoregressive Denoising Diffusion Models for Multivariate Probabilistic Time Series Forecasting","created":"2021-01-28","cited_by_count":337,"area":"diffusion"},{"id":"2204.00227","title":"Perception Prioritized Training of Diffusion Models","created":"2022-04-01","cited_by_count":303,"area":"diffusion"},{"id":"2311.14760","title":"SinSR: Diffusion-Based Image Super-Resolution in a Single Step","created":"2023-11-23","cited_by_count":238,"area":"diffusion"},{"id":"2205.07680","title":"BBDM: Image-to-image Translation with Brownian Bridge Diffusion Models","created":"2022-05-16","cited_by_count":225,"area":"diffusion"},{"id":"2303.16491","title":"Implicit Diffusion Models for Continuous Super-Resolution","created":"2023-03-29","cited_by_count":218,"area":"diffusion"},{"id":"2402.03290","title":"InstanceDiffusion: Instance-level Control for Image Generation","created":"2024-02-05","cited_by_count":175,"area":"diffusion"},{"id":"2303.14207","title":"DiffuScene: Denoising Diffusion Models for Generative Indoor Scene Synthesis","created":"2023-03-24","cited_by_count":166,"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":"2404.04650","title":"InitNO: Boosting Text-to-Image Diffusion Models via Initial Noise Optimization","created":"2024-04-06","cited_by_count":123,"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":"2307.10422","title":"PreDiff: Precipitation Nowcasting with Latent Diffusion Models","created":"2023-07-19","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":"2410.01756","title":"ImageFolder: Autoregressive Image Generation with Folded Tokens","created":"2024-10-02","cited_by_count":94,"area":"diffusion"},{"id":"2301.05221","title":"Open-vocabulary Object Segmentation with Diffusion Models","created":"2023-01-12","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":"2208.13753","title":"Frido: Feature Pyramid Diffusion for Complex Scene Image Synthesis","created":"2022-08-29","cited_by_count":75,"area":"diffusion"},{"id":"2311.18257","title":"Diffusion Models Without Attention","created":"2023-11-30","cited_by_count":75,"area":"diffusion"},{"id":"2310.15111","title":"Matryoshka Diffusion Models","created":"2023-10-23","cited_by_count":72,"area":"diffusion"},{"id":"2111.12701","title":"Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes","created":"2021-11-24","cited_by_count":71,"area":"diffusion"},{"id":"2503.04482","title":"Generalized Interpolating Discrete Diffusion","created":"2025-03-06","cited_by_count":70,"area":"diffusion"},{"id":"2406.09750","title":"ControlVAR: Exploring Controllable Visual Autoregressive Modeling","created":"2024-06-14","cited_by_count":58,"area":"diffusion"},{"id":"2212.12990","title":"Unsupervised Representation Learning from Pre-trained Diffusion Probabilistic Models","created":"2022-12-26","cited_by_count":54,"area":"diffusion"},{"id":"2305.03935","title":"Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs","created":"2023-05-06","cited_by_count":54,"area":"diffusion"},{"id":"2312.13236","title":"Diffusion Models With Learned Adaptive Noise","created":"2023-12-20","cited_by_count":51,"area":"diffusion"},{"id":"2311.17137","title":"Generative Models: What Do They Know? Do They Know Things? Let's Find Out!","created":"2023-11-28","cited_by_count":50,"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":"2309.07920","title":"Large-Vocabulary 3D Diffusion Model with Transformer","created":"2023-09-14","cited_by_count":48,"area":"diffusion"},{"id":"2410.02705","title":"ControlAR: Controllable Image Generation with Autoregressive Models","created":"2024-10-03","cited_by_count":48,"area":"diffusion"},{"id":"2202.09671","title":"Truncated Diffusion Probabilistic Models and Diffusion-based Adversarial Auto-Encoders","created":"2022-02-19","cited_by_count":42,"area":"diffusion"},{"id":"2112.01799","title":"Global Context with Discrete Diffusion in Vector Quantised Modelling for Image Generation","created":"2021-12-03","cited_by_count":40,"area":"diffusion"},{"id":"2211.14842","title":"Unified Discrete Diffusion for Simultaneous Vision-Language Generation","created":"2022-11-27","cited_by_count":39,"area":"diffusion"},{"id":"2305.18729","title":"Real-World Image Variation by Aligning Diffusion Inversion Chain","created":"2023-05-30","cited_by_count":37,"area":"diffusion"},{"id":"2306.00354","title":"Addressing Negative Transfer in Diffusion Models","created":"2023-06-01","cited_by_count":33,"area":"diffusion"},{"id":"2502.11564","title":"Continuous Diffusion Model for Language Modeling","created":"2025-02-17","cited_by_count":31,"area":"diffusion"},{"id":"2401.13115","title":"Contractive Diffusion Probabilistic Models","created":"2024-01-23","cited_by_count":29,"area":"diffusion"},{"id":"2409.19365","title":"Conditional Image Synthesis with Diffusion Models: A Survey","created":"2024-09-28","cited_by_count":29,"area":"diffusion"},{"id":"2206.00386","title":"DiVAE: Photorealistic Images Synthesis with Denoising Diffusion Decoder","created":"2022-06-01","cited_by_count":27,"area":"diffusion"},{"id":"2402.05937","title":"InstaGen: Enhancing Object Detection by Training on Synthetic Dataset","created":"2024-02-08","cited_by_count":26,"area":"diffusion"},{"id":"2106.15671","title":"Diffusion Priors In Variational Autoencoders","created":"2021-06-29","cited_by_count":25,"area":"diffusion"},{"id":"2203.04304","title":"Dynamic Dual-Output Diffusion Models","created":"2022-03-08","cited_by_count":25,"area":"diffusion"},{"id":"2305.11577","title":"LeftRefill: Filling Right Canvas based on Left Reference through Generalized Text-to-Image Diffusion Model","created":"2023-05-19","cited_by_count":25,"area":"diffusion"},{"id":"2211.03264","title":"Few-shot Image Generation with Diffusion Models","created":"2022-11-07","cited_by_count":21,"area":"diffusion"},{"id":"2306.05423","title":"ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process","created":"2023-06-08","cited_by_count":20,"area":"diffusion"},{"id":"2505.18495","title":"Beyond Masked and Unmasked: Discrete Diffusion Models via Partial Masking","created":"2025-05-24","cited_by_count":20,"area":"diffusion"},{"id":"2506.04421","title":"HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation","created":"2025-06-04","cited_by_count":20,"area":"diffusion"},{"id":"2412.14158","title":"AKiRa: Augmentation Kit on Rays for optical video generation","created":"2024-12-18","cited_by_count":18,"area":"diffusion"},{"id":"2412.17153","title":"Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching","created":"2024-12-22","cited_by_count":18,"area":"diffusion"},{"id":"2302.10907","title":"Diffusion Models in Bioinformatics: A New Wave of Deep Learning Revolution in Action","created":"2023-02-13","cited_by_count":15,"area":"diffusion"},{"id":"2306.14153","title":"DomainStudio: Fine-Tuning Diffusion Models for Domain-Driven Image Generation using Limited Data","created":"2023-06-25","cited_by_count":15,"area":"diffusion"},{"id":"2505.18047","title":"RestoreVAR: Visual Autoregressive Generation for All-in-One Image Restoration","created":"2025-05-23","cited_by_count":15,"area":"diffusion"},{"id":"2410.03755","title":"Denoising with a Joint-Embedding Predictive Architecture","created":"2024-10-02","cited_by_count":14,"area":"diffusion"},{"id":"2312.00210","title":"DREAM: Diffusion Rectification and Estimation-Adaptive Models","created":"2023-11-30","cited_by_count":12,"area":"diffusion"},{"id":"2502.15176","title":"Methods and Trends in Detecting AI-Generated Images: A Comprehensive Review","created":"2025-02-21","cited_by_count":12,"area":"diffusion"},{"id":"2308.11949","title":"High-quality Image Dehazing with Diffusion Model","created":"2023-08-23","cited_by_count":11,"area":"diffusion"},{"id":"2506.10962","title":"SpectralAR: Spectral Autoregressive Visual Generation","created":"2025-06-12","cited_by_count":11,"area":"diffusion"},{"id":"2504.10434","title":"Anchor Token Matching: Implicit Structure Locking for Training-free AR Image Editing","created":"2025-04-14","cited_by_count":10,"area":"diffusion"},{"id":"2403.05196","title":"Denoising Autoregressive Representation Learning","created":"2024-03-08","cited_by_count":9,"area":"diffusion"},{"id":"2405.08055","title":"DiffTF++: 3D-aware Diffusion Transformer for Large-Vocabulary 3D Generation","created":"2024-05-13","cited_by_count":9,"area":"diffusion"},{"id":"2504.11295","title":"Autoregressive Distillation of Diffusion Transformers","created":"2025-04-15","cited_by_count":9,"area":"diffusion"},{"id":"2506.01337","title":"NoiseAR: AutoRegressing Initial Noise Prior for Diffusion Models","created":"2025-06-02","cited_by_count":8,"area":"diffusion"},{"id":"2602.15030","title":"Image Generation with a Sphere Encoder","created":"2026-02-16","cited_by_count":8,"area":"diffusion"},{"id":"2308.10187","title":"Spiking-Diffusion: Vector Quantized Discrete Diffusion Model with Spiking Neural Networks","created":"2023-08-20","cited_by_count":7,"area":"diffusion"},{"id":"2401.02414","title":"Bring Metric Functions into Diffusion Models","created":"2024-01-04","cited_by_count":7,"area":"diffusion"},{"id":"2505.22306","title":"Versatile Cardiovascular Signal Generation with a Unified Diffusion Transformer","created":"2025-05-28","cited_by_count":7,"area":"diffusion"},{"id":"2510.20217","title":"EditInfinity: Image Editing with Binary-Quantized Generative Models","created":"2025-10-23","cited_by_count":7,"area":"diffusion"},{"id":"2403.16954","title":"Isolated Diffusion: Optimizing Multi-Concept Text-to-Image Generation Training-Freely with Isolated Diffusion Guidance","created":"2024-03-25","cited_by_count":6,"area":"diffusion"},{"id":"2405.14101","title":"Enhancing Image Layout Control with Loss-Guided Diffusion Models","created":"2024-05-23","cited_by_count":6,"area":"diffusion"},{"id":"2506.10433","title":"Measuring Semantic Information Production in Generative Diffusion Models","created":"2025-06-12","cited_by_count":6,"area":"diffusion"},{"id":"2506.19839","title":"Improving Progressive Generation with Decomposable Flow Matching","created":"2025-06-24","cited_by_count":6,"area":"diffusion"},{"id":"2403.04634","title":"Pix2Gif: Motion-Guided Diffusion for GIF Generation","created":"2024-03-07","cited_by_count":5,"area":"diffusion"},{"id":"2405.19201","title":"Going beyond Compositions, DDPMs Can Produce Zero-Shot Interpolations","created":"2024-05-29","cited_by_count":5,"area":"diffusion"},{"id":"2407.07174","title":"CamFreeDiff: Camera-free Image to Panorama Generation with Diffusion Model","created":"2024-07-09","cited_by_count":5,"area":"diffusion"},{"id":"2507.03054","title":"LATTE: Latent Trajectory Embedding for Diffusion-Generated Image Detection","created":"2025-07-03","cited_by_count":5,"area":"diffusion"},{"id":"2312.12431","title":"On Inference Stability for Diffusion Models","created":"2023-12-19","cited_by_count":4,"area":"diffusion"},{"id":"2402.11487","title":"Visual Concept-driven Image Generation with Text-to-Image Diffusion Model","created":"2024-02-18","cited_by_count":4,"area":"diffusion"},{"id":"2402.16369","title":"Generative AI in Vision: A Survey on Models, Metrics and Applications","created":"2024-02-26","cited_by_count":4,"area":"diffusion"},{"id":"2405.11605","title":"Switched Flow Matching: Eliminating Singularities via Switching ODEs","created":"2024-05-19","cited_by_count":4,"area":"diffusion"},{"id":"2503.09242","title":"NAMI: Efficient Image Generation via Bridged Progressive Rectified Flow Transformers","created":"2025-03-12","cited_by_count":4,"area":"diffusion"},{"id":"2506.09482","title":"Marrying Autoregressive Transformer and Diffusion with Multi-Reference Autoregression","created":"2025-06-11","cited_by_count":4,"area":"diffusion"},{"id":"2308.11948","title":"Efficient Transfer Learning in Diffusion Models via Adversarial Noise","created":"2023-08-23","cited_by_count":3,"area":"diffusion"},{"id":"2407.08659","title":"Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density","created":"2024-07-11","cited_by_count":3,"area":"diffusion"},{"id":"2503.04344","title":"LEDiT: Your Length-Extrapolatable Diffusion Transformer without Positional Encoding","created":"2025-03-06","cited_by_count":3,"area":"diffusion"},{"id":"2506.00849","title":"Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis","created":"2025-06-01","cited_by_count":3,"area":"diffusion"},{"id":"2604.20041","title":"Normalizing Flows with Iterative Denoising","created":"2026-04-21","cited_by_count":3,"area":"diffusion"},{"id":"2301.01206","title":"Speed up the inference of diffusion models via shortcut MCMC sampling","created":"2022-12-18","cited_by_count":2,"area":"diffusion"},{"id":"2403.01485","title":"Approximations to the Fisher Information Metric of Deep Generative Models for Out-Of-Distribution Detection","created":"2024-03-03","cited_by_count":2,"area":"diffusion"},{"id":"2408.09800","title":"Latent Diffusion for Guided Document Table Generation","created":"2024-08-19","cited_by_count":2,"area":"diffusion"}],"next_cursor":"100"}