{"total":79,"rows":[{"id":"2406.06525","title":"Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation","created":"2024-06-10","cited_by_count":777,"area":null},{"id":"2203.01941","title":"Autoregressive Image Generation using Residual Quantization","created":"2022-03-03","cited_by_count":722,"area":null},{"id":"2110.04627","title":"Vector-quantized Image Modeling with Improved VQGAN","created":"2021-10-09","cited_by_count":658,"area":null},{"id":"2202.00273","title":"StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets","created":"2022-02-01","cited_by_count":492,"area":null},{"id":"2211.09117","title":"MAGE: MAsked Generative Encoder to Unify Representation Learning and Image Synthesis","created":"2022-11-16","cited_by_count":227,"area":null},{"id":"2203.06026","title":"The Role of ImageNet Classes in Fr\\'echet Inception Distance","created":"2022-03-11","cited_by_count":213,"area":null},{"id":"2201.12204","title":"From data to functa: Your data point is a function and you can treat it like one","created":"2022-01-28","cited_by_count":187,"area":null},{"id":"2209.09002","title":"MoVQ: Modulating Quantized Vectors for High-Fidelity Image Generation","created":"2022-09-19","cited_by_count":125,"area":null},{"id":"2103.09396","title":"Pros and Cons of GAN Evaluation Measures: New Developments","created":"2021-03-17","cited_by_count":123,"area":null},{"id":"2108.08827","title":"ImageBART: Bidirectional Context with Multinomial Diffusion for Autoregressive Image Synthesis","created":"2021-08-19","cited_by_count":122,"area":null},{"id":"2201.10326","title":"ShapeFormer: Transformer-based Shape Completion via Sparse Representation","created":"2022-01-25","cited_by_count":106,"area":null},{"id":"2504.07963","title":"PixelFlow: Pixel-Space Generative Models with Flow","created":"2025-04-10","cited_by_count":97,"area":null},{"id":"2502.09509","title":"EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling","created":"2025-02-13","cited_by_count":89,"area":null},{"id":"2512.10794","title":"What matters for Representation Alignment: Global Information or Spatial Structure?","created":"2025-12-11","cited_by_count":84,"area":null},{"id":"2202.07765","title":"General-purpose, long-context autoregressive modeling with Perceiver AR","created":"2022-02-15","cited_by_count":60,"area":null},{"id":"2305.11718","title":"Towards Accurate Image Coding: Improved Autoregressive Image Generation with Dynamic Vector Quantization","created":"2023-05-19","cited_by_count":60,"area":null},{"id":"2411.05902","title":"Autoregressive Models in Vision: A Survey","created":"2024-11-08","cited_by_count":39,"area":null},{"id":"2203.09494","title":"Transframer: Arbitrary Frame Prediction with Generative Models","created":"2022-03-17","cited_by_count":37,"area":null},{"id":"2403.10075","title":"A survey of synthetic data augmentation methods in computer vision","created":"2024-03-15","cited_by_count":34,"area":null},{"id":"2204.08227","title":"The Devil is in the Frequency: Geminated Gestalt Autoencoder for Self-Supervised Visual Pre-Training","created":"2022-04-18","cited_by_count":33,"area":null},{"id":"2406.09415","title":"An Image is Worth More Than 16x16 Patches: Exploring Transformers on Individual Pixels","created":"2024-06-13","cited_by_count":33,"area":null},{"id":"2206.00070","title":"On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models","created":"2022-05-31","cited_by_count":31,"area":null},{"id":"2212.03185","title":"Rethinking the Objectives of Vector-Quantized Tokenizers for Image Synthesis","created":"2022-12-06","cited_by_count":31,"area":null},{"id":"2305.13607","title":"Not All Image Regions Matter: Masked Vector Quantization for Autoregressive Image Generation","created":"2023-05-23","cited_by_count":28,"area":null},{"id":"2403.00522","title":"VisionLLaMA: A Unified LLaMA Backbone for Vision Tasks","created":"2024-03-01","cited_by_count":28,"area":null},{"id":"2412.12441","title":"Numerical Pruning for Efficient Autoregressive Models","created":"2024-12-17","cited_by_count":25,"area":null},{"id":"2103.06089","title":"Variable-rate discrete representation learning","created":"2021-03-10","cited_by_count":24,"area":null},{"id":"2203.01993","title":"Polarity Sampling: Quality and Diversity Control of Pre-Trained Generative Networks via Singular Values","created":"2022-03-03","cited_by_count":21,"area":null},{"id":"2303.11424","title":"Polynomial Implicit Neural Representations For Large Diverse Datasets","created":"2023-03-20","cited_by_count":18,"area":null},{"id":"2111.11672","title":"Few-shot Image Generation with Mixup-based Distance Learning","created":"2021-11-23","cited_by_count":16,"area":null},{"id":"2410.22655","title":"FlowDCN: Exploring DCN-like Architectures for Fast Image Generation with Arbitrary Resolution","created":"2024-10-30","cited_by_count":16,"area":null},{"id":"2412.09607","title":"Spectral Image Tokenizer","created":"2024-12-12","cited_by_count":15,"area":null},{"id":"2506.03131","title":"Native-Resolution Image Synthesis","created":"2025-06-03","cited_by_count":15,"area":null},{"id":"2305.03901","title":"Synthesizing PET images from High-field and Ultra-high-field MR images Using Joint Diffusion Attention Model","created":"2023-05-06","cited_by_count":14,"area":null},{"id":"2111.12994","title":"NomMer: Nominate Synergistic Context in Vision Transformer for Visual Recognition","created":"2021-11-25","cited_by_count":12,"area":null},{"id":"2208.04139","title":"DALLE-URBAN: Capturing the urban design expertise of large text to image transformers","created":"2022-08-03","cited_by_count":12,"area":null},{"id":"2505.07175","title":"Metrics that matter: Evaluating image quality metrics for medical image generation","created":"2025-05-12","cited_by_count":12,"area":null},{"id":"2111.10800","title":"FreqNet: A Frequency-domain Image Super-Resolution Network with Dicrete Cosine Transform","created":"2021-11-21","cited_by_count":11,"area":null},{"id":"2306.10987","title":"A VAE Approach to Sample Multivariate Extremes","created":"2023-06-19","cited_by_count":10,"area":null},{"id":"2405.18616","title":"Wavelet-Based Image Tokenizer for Vision Transformers","created":"2024-05-28","cited_by_count":10,"area":null},{"id":"2408.07337","title":"KIND: Knowledge Integration and Diversion for Training Decomposable Models","created":"2024-08-14","cited_by_count":10,"area":null},{"id":"2410.01322","title":"Forte : Finding Outliers with Representation Typicality Estimation","created":"2024-10-02","cited_by_count":9,"area":null},{"id":"2509.01109","title":"GPSToken: Gaussian Parameterized Spatially-adaptive Tokenization for Image Representation and Generation","created":"2025-09-01","cited_by_count":9,"area":null},{"id":"2404.00633","title":"IPT-V2: Efficient Image Processing Transformer using Hierarchical Attentions","created":"2024-03-31","cited_by_count":7,"area":null},{"id":"2304.01064","title":"Real-time 6K Image Rescaling with Rate-distortion Optimization","created":"2023-04-03","cited_by_count":6,"area":null},{"id":"2504.10188","title":"Efficient Generative Model Training via Embedded Representation Warmup","created":"2025-04-14","cited_by_count":6,"area":null},{"id":"2211.14308","title":"WALDO: Future Video Synthesis using Object Layer Decomposition and Parametric Flow Prediction","created":"2022-11-25","cited_by_count":5,"area":null},{"id":"2502.06516","title":"Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation","created":"2025-02-10","cited_by_count":5,"area":null},{"id":"2602.09009","title":"ANCRe: Adaptive Neural Connection Reassignment for Efficient Depth Scaling","created":"2026-02-09","cited_by_count":5,"area":null},{"id":"2501.12381","title":"Parallel Sequence Modeling via Generalized Spatial Propagation Network","created":"2025-01-21","cited_by_count":4,"area":null},{"id":"2111.01785","title":"PatchGame: Learning to Signal Mid-level Patches in Referential Games","created":"2021-11-02","cited_by_count":3,"area":null},{"id":"2205.12533","title":"Structured Uncertainty in the Observation Space of Variational Autoencoders","created":"2022-05-25","cited_by_count":3,"area":null},{"id":"2306.01999","title":"GAT-GAN : A Graph-Attention-based Time-Series Generative Adversarial Network","created":"2023-06-03","cited_by_count":3,"area":null},{"id":"2308.09110","title":"JPEG Quantized Coefficient Recovery via DCT Domain Spatial-Frequential Transformer","created":"2023-08-17","cited_by_count":3,"area":null},{"id":"2311.13620","title":"The Challenges of Image Generation Models in Generating Multi-Component Images","created":"2023-11-22","cited_by_count":3,"area":null},{"id":"2410.21262","title":"BLAST: Block-Level Adaptive Structured Matrices for Efficient Deep Neural Network Inference","created":"2024-10-28","cited_by_count":3,"area":null},{"id":"2111.12577","title":"A Method for Evaluating Deep Generative Models of Images via Assessing the Reproduction of High-order Spatial Context","created":"2021-11-24","cited_by_count":2,"area":null},{"id":"2402.04646","title":"Block Sparse Bayesian Learning: A Diversified Scheme","created":"2024-02-07","cited_by_count":2,"area":null},{"id":"2511.22345","title":"Flowing Backwards: Improving Normalizing Flows via Reverse Representation Alignment","created":"2025-11-27","cited_by_count":2,"area":null},{"id":"2601.14671","title":"Mirai: Autoregressive Visual Generation Needs Foresight","created":"2026-01-21","cited_by_count":2,"area":null},{"id":"2605.27919","title":"Frequency-Guided Action Diffusion via Sub-Frequency Manifold Traversal","created":"2026-05-27","cited_by_count":2,"area":null},{"id":"2606.31029","title":"TerraDiT-$\\Omega$: Unified Spatial Control for Satellite Image Synthesis with Any Geospatial Primitive","created":"2026-06-30","cited_by_count":2,"area":null},{"id":"2307.08526","title":"Image Captions are Natural Prompts for Text-to-Image Models","created":"2023-07-17","cited_by_count":1,"area":null},{"id":"2308.15472","title":"Learning Modulated Transformation in GANs","created":"2023-08-29","cited_by_count":1,"area":null},{"id":"2407.20553","title":"DiffusionCounterfactuals: Inferring High-dimensional Counterfactuals with Guidance of Causal Representations","created":"2024-07-30","cited_by_count":1,"area":null},{"id":"2509.01421","title":"InfoScale: Unleashing Training-free Variable-scaled Image Generation via Effective Utilization of Information","created":"2025-09-01","cited_by_count":1,"area":null},{"id":"2509.15591","title":"Latent Zoning Network: A Unified Principle for Generative Modeling, Representation Learning, and Classification","created":"2025-09-19","cited_by_count":1,"area":null},{"id":"2512.19311","title":"MixFlow Training: Alleviating Exposure Bias with Slowed Interpolation Mixture","created":"2025-12-22","cited_by_count":1,"area":null},{"id":"2205.09731","title":"Towards Unified Keyframe Propagation Models","created":"2022-05-19","cited_by_count":0,"area":null},{"id":"2208.11673","title":"Learned Lossless JPEG Transcoding via Joint Lossy and Residual Compression","created":"2022-08-24","cited_by_count":0,"area":null},{"id":"2309.06721","title":"Dynamic Spectrum Mixer for Visual Recognition","created":"2023-09-13","cited_by_count":0,"area":null},{"id":"2504.20800","title":"Adept: Annotation-Denoising Auxiliary Tasks with Discrete Cosine Transform Map and Keypoint for Human-Centric Pretraining","created":"2025-04-29","cited_by_count":0,"area":null},{"id":"2601.22630","title":"LINA: Linear Autoregressive Image Generative Models with Continuous Tokens","created":"2026-01-30","cited_by_count":0,"area":null},{"id":"2604.07397","title":"Data Warmup: Complexity-Aware Curricula for Efficient Diffusion Training","created":"2026-04-08","cited_by_count":0,"area":null},{"id":"2605.16384","title":"Mutual Enhancement Between Global Tokens and Patch Tokens: From Theory to Practice","created":"2026-05-11","cited_by_count":0,"area":null},{"id":"2606.23000","title":"MotionMAR: Multi-scale Auto-Regressive Human Motion Reconstruction from Sparse Observations","created":"2026-06-22","cited_by_count":0,"area":null},{"id":"2609.33601","title":"JustQuant: You Don't Need Smoothing, SVD, or Rotation for 4-Bit Activation Quantization","created":"2026-09-27","cited_by_count":0,"area":null},{"id":"2610.05711","title":"From Pixels, Without Pre-training: Joint Generative and Self-Supervised Representation Learning in One Model","created":"2026-10-05","cited_by_count":0,"area":null},{"id":"2610.12843","title":"APEX: Asynchronous Prefix Denoising for Extreme Compression","created":"2026-10-09","cited_by_count":0,"area":null}],"next_cursor":null}