{"total":144,"rows":[{"id":"2409.18869","title":"Emu3: Next-Token Prediction is All You Need","created":"2024-09-27","cited_by_count":781,"area":"diffusion"},{"id":"2501.01423","title":"Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models","created":"2025-01-02","cited_by_count":393,"area":"diffusion"},{"id":"2409.04429","title":"VILA-U: a Unified Foundation Model Integrating Visual Understanding and Generation","created":"2024-09-06","cited_by_count":295,"area":"diffusion"},{"id":"2505.15809","title":"MMaDA: Multimodal Large Diffusion Language Models","created":"2025-05-21","cited_by_count":250,"area":"diffusion"},{"id":"2506.15564","title":"Show-o2: Improved Native Unified Multimodal Models","created":"2025-06-18","cited_by_count":250,"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":"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":"2410.10812","title":"HART: Efficient Visual Generation with Hybrid Autoregressive Transformer","created":"2024-10-14","cited_by_count":132,"area":"diffusion"},{"id":"2504.05741","title":"DDT: Decoupled Diffusion Transformer","created":"2025-04-08","cited_by_count":109,"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":"2410.01756","title":"ImageFolder: Autoregressive Image Generation with Folded Tokens","created":"2024-10-02","cited_by_count":94,"area":"diffusion"},{"id":"2411.13807","title":"MagicDrive-V2: High-Resolution Long Video Generation for Autonomous Driving with Adaptive Control","created":"2024-11-21","cited_by_count":92,"area":"diffusion"},{"id":"2510.06308","title":"Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understanding","created":"2025-10-07","cited_by_count":88,"area":"diffusion"},{"id":"2510.15301","title":"Latent Diffusion Model without Variational Autoencoder","created":"2025-10-17","cited_by_count":88,"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":"2502.04896","title":"Goku: Flow Based Video Generative Foundation Models","created":"2025-02-07","cited_by_count":67,"area":"diffusion"},{"id":"2407.11633","title":"Scaling Diffusion Transformers to 16 Billion Parameters","created":"2024-07-16","cited_by_count":66,"area":"diffusion"},{"id":"2412.03293","title":"Diffusion-VLA: Generalizable and Interpretable Robot Foundation Model via Self-Generated Reasoning","created":"2024-12-04","cited_by_count":57,"area":"diffusion"},{"id":"2412.03487","title":"Flow Matching with General Discrete Paths: A Kinetic-Optimal Perspective","created":"2024-12-04","cited_by_count":57,"area":"diffusion"},{"id":"2508.10711","title":"NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scale","created":"2025-08-14","cited_by_count":57,"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":"2505.23606","title":"Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Model","created":"2025-05-29","cited_by_count":55,"area":"diffusion"},{"id":"2410.20280","title":"MarDini: Masked Autoregressive Diffusion for Video Generation at Scale","created":"2024-10-26","cited_by_count":49,"area":"diffusion"},{"id":"2503.20853","title":"Unified Multimodal Discrete Diffusion","created":"2025-03-26","cited_by_count":49,"area":"diffusion"},{"id":"2410.02705","title":"ControlAR: Controllable Image Generation with Autoregressive Models","created":"2024-10-03","cited_by_count":48,"area":"diffusion"},{"id":"2410.03355","title":"LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding","created":"2024-10-04","cited_by_count":47,"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":"2502.04847","title":"HumanDiT: Pose-Guided Diffusion Transformer for Long-form Human Motion Video Generation","created":"2025-02-07","cited_by_count":39,"area":"diffusion"},{"id":"2504.07960","title":"VisualCloze: A Universal Image Generation Framework via Visual In-Context Learning","created":"2025-04-10","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":"2503.11056","title":"Flow to the Mode: Mode-Seeking Diffusion Autoencoders for State-of-the-Art Image Tokenization","created":"2025-03-14","cited_by_count":36,"area":"diffusion"},{"id":"2509.04394","title":"Transition Models: Rethinking the Generative Learning Objective","created":"2025-09-04","cited_by_count":34,"area":"diffusion"},{"id":"2410.08159","title":"DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation","created":"2024-10-10","cited_by_count":32,"area":"diffusion"},{"id":"2412.12095","title":"Causal Diffusion Transformers for Generative Modeling","created":"2024-12-16","cited_by_count":31,"area":"diffusion"},{"id":"2410.04671","title":"CAR: Controllable Autoregressive Modeling for Visual Generation","created":"2024-10-07","cited_by_count":30,"area":"diffusion"},{"id":"2504.09975","title":"OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generation","created":"2025-04-14","cited_by_count":30,"area":"diffusion"},{"id":"2512.07829","title":"One Layer Is Enough: Adapting Pretrained Visual Encoders for Image Generation","created":"2025-12-08","cited_by_count":28,"area":"diffusion"},{"id":"2503.11073","title":"Perceive, Understand and Restore: Real-World Image Super-Resolution with Autoregressive Multimodal Generative Models","created":"2025-03-14","cited_by_count":24,"area":"diffusion"},{"id":"2503.14487","title":"DiffMoE: Dynamic Token Selection for Scalable Diffusion Transformers","created":"2025-03-18","cited_by_count":24,"area":"diffusion"},{"id":"2507.08801","title":"Lumos-1: On Autoregressive Video Generation with Discrete Diffusion from a Unified Model Perspective","created":"2025-07-11","cited_by_count":22,"area":"diffusion"},{"id":"2508.15772","title":"Visual Autoregressive Modeling for Instruction-Guided Image Editing","created":"2025-08-21","cited_by_count":22,"area":"diffusion"},{"id":"2503.10704","title":"Error Analyses of Auto-Regressive Video Diffusion Models: A Unified Framework","created":"2025-03-12","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":"2412.17153","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":"2502.20172","title":"Multimodal Representation Alignment for Image Generation: Text-Image Interleaved Control Is Easier Than You Think","created":"2025-02-27","cited_by_count":18,"area":"diffusion"},{"id":"2508.07747","title":"Grouped Speculative Decoding for Autoregressive Image Generation","created":"2025-08-11","cited_by_count":17,"area":"diffusion"},{"id":"2510.18457","title":"VFM-VAE: Vision Foundation Models Can Be Good Tokenizers for Latent Diffusion Models","created":"2025-10-21","cited_by_count":17,"area":"diffusion"},{"id":"2509.24335","title":"Hyperspherical Latents Improve Continuous-Token Autoregressive Generation","created":"2025-09-29","cited_by_count":16,"area":"diffusion"},{"id":"2507.20454","title":"Frequency-Aware Autoregressive Modeling for Efficient High-Resolution Image Synthesis","created":"2025-07-28","cited_by_count":15,"area":"diffusion"},{"id":"2503.07197","title":"Effective and Efficient Masked Image Generation Models","created":"2025-03-10","cited_by_count":13,"area":"diffusion"},{"id":"2506.05501","title":"FocusDiff: Advancing Fine-Grained Text-Image Alignment for Autoregressive Visual Generation through RL","created":"2025-06-05","cited_by_count":13,"area":"diffusion"},{"id":"2512.15657","title":"SoFlow: Solution Flow Models for One-Step Generative Modeling","created":"2025-12-17","cited_by_count":13,"area":"diffusion"},{"id":"2510.24717","title":"Uniform Discrete Diffusion with Metric Path for Video Generation","created":"2025-10-28","cited_by_count":12,"area":"diffusion"},{"id":"2512.11715","title":"EditMGT: Unleashing Potentials of Masked Generative Transformers in Image Editing","created":"2025-12-12","cited_by_count":12,"area":"diffusion"},{"id":"2512.11749","title":"SVG-T2I: Scaling Up Text-to-Image Latent Diffusion Model Without Variational Autoencoder","created":"2025-12-12","cited_by_count":12,"area":"diffusion"},{"id":"2408.09027","title":"Efficient Autoregressive Audio Modeling via Next-Scale Prediction","created":"2024-08-16","cited_by_count":11,"area":"diffusion"},{"id":"2412.06787","title":"[MASK] is All You Need","created":"2024-12-09","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":"2506.23589","title":"Transition Matching: Scalable and Flexible Generative Modeling","created":"2025-06-30","cited_by_count":11,"area":"diffusion"},{"id":"2501.12976","title":"LiT: Delving into a Simple Linear Diffusion Transformer for Image Generation","created":"2025-01-22","cited_by_count":10,"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":"2508.08098","title":"TBAC-UniImage: Unified Understanding and Generation by Ladder-Side Diffusion Tuning","created":"2025-08-11","cited_by_count":10,"area":"diffusion"},{"id":"2603.02943","title":"TC-Pad\\'e: Trajectory-Consistent Pad\\'e Approximation for Diffusion Acceleration","created":"2026-03-03","cited_by_count":10,"area":"diffusion"},{"id":"2504.09454","title":"D$^2$iT: Dynamic Diffusion Transformer for Accurate Image Generation","created":"2025-04-13","cited_by_count":9,"area":"diffusion"},{"id":"2602.07022","title":"Condition Errors Refinement in Autoregressive Image Generation with Diffusion Loss","created":"2026-02-02","cited_by_count":9,"area":"diffusion"},{"id":"2605.15741","title":"HyperDiT: Hyper-Connected Transformers for High-Fidelity Pixel-Space Diffusion","created":"2026-05-15","cited_by_count":9,"area":"diffusion"},{"id":"2410.07659","title":"MotionAura: Generating High-Quality and Motion Consistent Videos using Discrete Diffusion","created":"2024-10-10","cited_by_count":7,"area":"diffusion"},{"id":"2411.10781","title":"Bag of Design Choices for Inference of High-Resolution Masked Generative Transformer","created":"2024-11-16","cited_by_count":7,"area":"diffusion"},{"id":"2509.01984","title":"Discrete Noise Inversion for Next-scale Autoregressive Text-based Image Editing","created":"2025-09-02","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":"2601.05966","title":"VideoAR: Autoregressive Video Generation via Next-Frame & Scale Prediction","created":"2026-01-09","cited_by_count":7,"area":"diffusion"},{"id":"2603.19206","title":"RPiAE: A Representation-Pivoted Autoencoder Enhancing Both Image Generation and Editing","created":"2026-03-19","cited_by_count":7,"area":"diffusion"},{"id":"2605.23902","title":"PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion","created":"2026-05-22","cited_by_count":7,"area":"diffusion"},{"id":"2409.17565","title":"Pixel-Space Post-Training of Latent Diffusion Models","created":"2024-09-26","cited_by_count":6,"area":"diffusion"},{"id":"2503.10125","title":"Proxy-Tuning: Tailoring Multimodal Autoregressive Models for Subject-Driven Image Generation","created":"2025-03-13","cited_by_count":6,"area":"diffusion"},{"id":"2505.11196","title":"DiCo: Revitalizing ConvNets for Scalable and Efficient Diffusion Modeling","created":"2025-05-16","cited_by_count":6,"area":"diffusion"},{"id":"2507.13984","title":"CSD-VAR: Content-Style Decomposition in Visual Autoregressive Models","created":"2025-07-18","cited_by_count":6,"area":"diffusion"},{"id":"2509.21912","title":"Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching","created":"2025-09-26","cited_by_count":6,"area":"diffusion"},{"id":"2509.22925","title":"Soft-Di[M]O: Improving One-Step Discrete Image Generation with Soft Embeddings","created":"2025-09-26","cited_by_count":6,"area":"diffusion"},{"id":"2602.19461","title":"Laplacian Multi-scale Flow Matching for Generative Modeling","created":"2026-02-23","cited_by_count":6,"area":"diffusion"},{"id":"2410.00350","title":"Efficient Training of Large Vision Models via Advanced Automated Progressive Learning","created":"2024-09-06","cited_by_count":5,"area":"diffusion"},{"id":"2410.22775","title":"Diffusion Beats Autoregressive: An Evaluation of Compositional Generation in Text-to-Image Models","created":"2024-10-30","cited_by_count":5,"area":"diffusion"},{"id":"2503.15457","title":"Di$\\mathtt{[M]}$O: Distilling Masked Diffusion Models into One-step Generator","created":"2025-03-19","cited_by_count":5,"area":"diffusion"},{"id":"2503.20198","title":"Beyond Words: Advancing Long-Text Image Generation via Multimodal Autoregressive Models","created":"2025-03-26","cited_by_count":5,"area":"diffusion"},{"id":"2505.08803","title":"Multi-modal Synthetic Data Training and Model Collapse: Insights from VLMs and Diffusion Models","created":"2025-05-10","cited_by_count":5,"area":"diffusion"},{"id":"2505.12274","title":"Context-Aware Autoregressive Models for Multi-Conditional Image Generation","created":"2025-05-18","cited_by_count":5,"area":"diffusion"},{"id":"2409.15010","title":"DepthART: Monocular Depth Estimation as Autoregressive Refinement Task","created":"2024-09-23","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":"2503.17804","title":"DVG-Diffusion: Dual-View Guided Diffusion Model for CT Reconstruction from X-Rays","created":"2025-03-22","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":"2509.10441","title":"InfGen: A Resolution-Agnostic Paradigm for Scalable Image Synthesis","created":"2025-09-12","cited_by_count":4,"area":"diffusion"},{"id":"2510.01478","title":"Purrception: Variational Flow Matching for Vector-Quantized Image Generation","created":"2025-10-01","cited_by_count":4,"area":"diffusion"},{"id":"2510.27135","title":"E-MMDiT: Revisiting Multimodal Diffusion Transformer Design for Fast Image Synthesis under Limited Resources","created":"2025-10-31","cited_by_count":4,"area":"diffusion"},{"id":"2601.05823","title":"Boosting Latent Diffusion Models via Disentangled Representation Alignment","created":"2026-01-09","cited_by_count":4,"area":"diffusion"},{"id":"2601.17124","title":"iFSQ: Improving FSQ for Image Generation with 1 Line of Code","created":"2026-01-23","cited_by_count":4,"area":"diffusion"},{"id":"2606.16255","title":"UniDDT: Unifying Multimodal Understanding and Generation with Decoupled Diffusion Transformer","created":"2026-06-15","cited_by_count":4,"area":"diffusion"},{"id":"2411.12523","title":"Data Pruning in Generative Diffusion Models","created":"2024-11-19","cited_by_count":3,"area":"diffusion"},{"id":"2502.18302","title":"LDGen: Enhancing Text-to-Image Synthesis via Large Language Model-Driven Language Representation","created":"2025-02-25","cited_by_count":3,"area":"diffusion"},{"id":"2505.19656","title":"ReDDiT: Rehashing Noise for Discrete Visual Generation","created":"2025-05-26","cited_by_count":3,"area":"diffusion"}],"next_cursor":"100"}