{"list":"other","total":65,"rows":[{"id":"2112.10752","title":"High-Resolution Image Synthesis with Latent Diffusion Models","created":"2021-12-20","cited_by_count":18863},{"id":"1801.03924","title":"The Unreasonable Effectiveness of Deep Features as a Perceptual Metric","created":"2018-01-11","cited_by_count":11177},{"id":"2105.05233","title":"Diffusion Models Beat GANs on Image Synthesis","created":"2021-05-11","cited_by_count":8255},{"id":"2104.14294","title":"Emerging Properties in Self-Supervised Vision Transformers","created":"2021-04-29","cited_by_count":6968},{"id":"2212.09748","title":"Scalable Diffusion Models with Transformers","created":"2022-12-19","cited_by_count":6054},{"id":"2207.12598","title":"Classifier-Free Diffusion Guidance","created":"2022-07-26","cited_by_count":5847},{"id":"2203.00667","title":"Generative Adversarial Networks","created":"2022-03-01","cited_by_count":5627},{"id":"1606.03498","title":"Improved Techniques for Training GANs","created":"2016-06-10","cited_by_count":2970},{"id":"1809.11096","title":"Large Scale GAN Training for High Fidelity Natural Image Synthesis","created":"2018-09-28","cited_by_count":2626},{"id":"1505.05770","title":"Variational Inference with Normalizing Flows","created":"2015-05-21","cited_by_count":2170},{"id":"1605.08803","title":"Density estimation using Real NVP","created":"2016-05-27","cited_by_count":2042},{"id":"1807.03039","title":"Glow: Generative Flow with Invertible 1x1 Convolutions","created":"2018-07-09","cited_by_count":1545},{"id":"1912.02762","title":"Normalizing Flows for Probabilistic Modeling and Inference","created":"2019-12-05","cited_by_count":1323},{"id":"1410.8516","title":"NICE: Non-linear Independent Components Estimation","created":"2014-10-30","cited_by_count":1058},{"id":"2404.02905","title":"Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction","created":"2024-04-03","cited_by_count":1023},{"id":"1601.06759","title":"Pixel Recurrent Neural Networks","created":"2016-01-25","cited_by_count":816},{"id":"2406.06525","title":"Autoregressive Model Beats Diffusion: Llama for Scalable Image Generation","created":"2024-06-10","cited_by_count":777},{"id":"2401.08740","title":"SiT: Exploring Flow and Diffusion-based Generative Models with Scalable Interpolant Transformers","created":"2024-01-16","cited_by_count":737},{"id":"2410.06940","title":"Representation Alignment for Generation: Training Diffusion Transformers Is Easier Than You Think","created":"2024-10-09","cited_by_count":703},{"id":"1705.07057","title":"Masked Autoregressive Flow for Density Estimation","created":"2017-05-19","cited_by_count":684},{"id":"2406.11838","title":"Autoregressive Image Generation without Vector Quantization","created":"2024-06-17","cited_by_count":651},{"id":"1606.04934","title":"Improving Variational Inference with Inverse Autoregressive Flow","created":"2016-06-15","cited_by_count":640},{"id":"2310.05737","title":"Language Model Beats Diffusion -- Tokenizer is Key to Visual Generation","created":"2023-10-09","cited_by_count":640},{"id":"2106.05931","title":"Score-based Generative Modeling in Latent Space","created":"2021-06-10","cited_by_count":636},{"id":"2209.12152","title":"All are Worth Words: A ViT Backbone for Diffusion Models","created":"2022-09-25","cited_by_count":502},{"id":"2202.00273","title":"StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets","created":"2022-02-01","cited_by_count":492},{"id":"2312.02696","title":"Analyzing and Improving the Training Dynamics of Diffusion Models","created":"2023-12-05","cited_by_count":402},{"id":"2501.01423","title":"Reconstruction vs. Generation: Taming Optimization Dilemma in Latent Diffusion Models","created":"2025-01-02","cited_by_count":393},{"id":"2510.11690","title":"Diffusion Transformers with Representation Autoencoders","created":"2025-10-13","cited_by_count":295},{"id":"2303.14389","title":"MDTv2: Masked Diffusion Transformer is a Strong Image Synthesizer","created":"2023-03-25","cited_by_count":262},{"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},{"id":"1804.00779","title":"Neural Autoregressive Flows","created":"2018-04-03","cited_by_count":208},{"id":"2212.11972","title":"Scalable Adaptive Computation for Iterative Generation","created":"2022-12-22","cited_by_count":195},{"id":"2306.09305","title":"Fast Training of Diffusion Models with Masked Transformers","created":"2023-06-15","cited_by_count":176},{"id":"2006.10605","title":"Riemannian Continuous Normalizing Flows","created":"2020-06-18","cited_by_count":145},{"id":"2312.02139","title":"DiffiT: Diffusion Vision Transformers for Image Generation","created":"2023-12-04","cited_by_count":106},{"id":"2504.07963","title":"PixelFlow: Pixel-Space Generative Models with Flow","created":"2025-04-10","cited_by_count":97},{"id":"2412.06329","title":"Normalizing Flows are Capable Generative Models","created":"2024-12-09","cited_by_count":91},{"id":"2502.09509","title":"EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling","created":"2025-02-13","cited_by_count":89},{"id":"2412.01827","title":"RandAR: Decoder-only Autoregressive Visual Generation in Random Orders","created":"2024-12-02","cited_by_count":83},{"id":"2507.23268","title":"PixNerd: Pixel Neural Field Diffusion","created":"2025-07-31","cited_by_count":82},{"id":"2412.15205","title":"FlowAR: Scale-wise Autoregressive Image Generation Meets Flow Matching","created":"2024-12-19","cited_by_count":80},{"id":"2502.14831","title":"Improving the Diffusability of Autoencoders","created":"2025-02-20","cited_by_count":80},{"id":"2410.19324","title":"Simpler Diffusion (SiD2): 1.5 FID on ImageNet512 with pixel-space diffusion","created":"2024-10-25","cited_by_count":75},{"id":"2502.20388","title":"Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation","created":"2025-02-27","cited_by_count":71},{"id":"2508.10711","title":"NextStep-1: Toward Autoregressive Image Generation with Continuous Tokens at Scale","created":"2025-08-14","cited_by_count":57},{"id":"2403.18103","title":"Tutorial on Diffusion Models for Imaging and Vision","created":"2024-03-26","cited_by_count":49},{"id":"2412.08635","title":"Multimodal Latent Language Modeling with Next-Token Diffusion","created":"2024-12-11","cited_by_count":48},{"id":"2411.19722","title":"JetFormer: An Autoregressive Generative Model of Raw Images and Text","created":"2024-11-29","cited_by_count":46},{"id":"2410.08159","title":"DART: Denoising Autoregressive Transformer for Scalable Text-to-Image Generation","created":"2024-10-10","cited_by_count":32},{"id":"2506.06276","title":"STARFlow: Scaling Latent Normalizing Flows for High-resolution Image Synthesis","created":"2025-06-06","cited_by_count":32},{"id":"2310.16624","title":"Free-form Flows: Make Any Architecture a Normalizing Flow","created":"2023-10-25","cited_by_count":26},{"id":"2506.21170","title":"Cosmos: Compressed and Smooth Latent Space for Text Diffusion Modeling","created":"2025-06-26","cited_by_count":25},{"id":"2507.15856","title":"Latent Denoising Makes Good Tokenizers","created":"2025-07-21","cited_by_count":20},{"id":"2402.06578","title":"On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows","created":"2024-02-09","cited_by_count":18},{"id":"2510.23588","title":"FARMER: Flow AutoRegressive Transformer over Pixels","created":"2025-10-27","cited_by_count":18},{"id":"2509.24335","title":"Hyperspherical Latents Improve Continuous-Token Autoregressive Generation","created":"2025-09-29","cited_by_count":16},{"id":"2405.21048","title":"Kaleido Diffusion: Improving Conditional Diffusion Models with Autoregressive Latent Modeling","created":"2024-05-31","cited_by_count":13},{"id":"2509.12474","title":"Image Tokenizer Needs Post-Training","created":"2025-09-15","cited_by_count":12},{"id":"1809.05861","title":"f-VAEs: Improve VAEs with Conditional Flows","created":"2018-09-16","cited_by_count":10},{"id":"2511.20462","title":"STARFlow-V: End-to-End Video Generative Modeling with Normalizing Flows","created":"2025-11-25","cited_by_count":9},{"id":"2507.00425","title":"Flexible Language Modeling in Continuous Space with Transformer-based Autoregressive Flows","created":"2025-07-01","cited_by_count":8},{"id":"2401.01855","title":"Transformer Neural Autoregressive Flows","created":"2024-01-03","cited_by_count":7},{"id":"2404.03109","title":"Many-to-many Image Generation with Auto-regressive Diffusion Models","created":"2024-04-03","cited_by_count":6},{"id":"2205.15209","title":"Flowification: Everything is a Normalizing Flow","created":"2022-05-30","cited_by_count":5}],"next_cursor":null}