{"total":295,"rows":[{"id":"2505.13447","title":"Mean Flows for One-step Generative Modeling","created":"2025-05-19","cited_by_count":561,"area":null},{"id":"2504.13181","title":"Perception Encoder: The best visual embeddings are not at the output of the network","created":"2025-04-17","cited_by_count":326,"area":null},{"id":"2504.11346","title":"Seedream 3.0 Technical Report","created":"2025-04-15","cited_by_count":154,"area":null},{"id":"2502.20321","title":"UniTok: A Unified Tokenizer for Visual Generation and Understanding","created":"2025-02-27","cited_by_count":153,"area":null},{"id":"2602.04770","title":"Generative Modeling via Drifting","created":"2026-02-04","cited_by_count":116,"area":null},{"id":"2512.02012","title":"Improved Mean Flows: On the Challenges of Fastforward Generative Models","created":"2025-12-01","cited_by_count":110,"area":null},{"id":"2505.05472","title":"Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation","created":"2025-05-08","cited_by_count":109,"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":"2505.02567","title":"Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities","created":"2025-05-05","cited_by_count":85,"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":"2502.20388","title":"Beyond Next-Token: Next-X Prediction for Autoregressive Visual Generation","created":"2025-02-27","cited_by_count":71,"area":null},{"id":"2504.08736","title":"GigaTok: Scaling Visual Tokenizers to 3 Billion Parameters for Autoregressive Image Generation","created":"2025-04-11","cited_by_count":57,"area":null},{"id":"2412.10958","title":"SoftVQ-VAE: Efficient 1-Dimensional Continuous Tokenizer","created":"2024-12-14","cited_by_count":56,"area":null},{"id":"2601.22158","title":"One-step Latent-free Image Generation with Pixel Mean Flows","created":"2026-01-29","cited_by_count":53,"area":null},{"id":"2508.15761","title":"Waver: Wave Your Way to Lifelike Video Generation","created":"2025-08-21","cited_by_count":52,"area":null},{"id":"2509.07295","title":"Reconstruction Alignment Improves Unified Multimodal Models","created":"2025-09-08","cited_by_count":49,"area":null},{"id":"2604.28190","title":"Representation Fr\\'echet Loss for Visual Generation","created":"2026-04-30","cited_by_count":37,"area":null},{"id":"2412.05796","title":"Language-Guided Image Tokenization for Generation","created":"2024-12-08","cited_by_count":36,"area":null},{"id":"2512.02014","title":"TUNA: Taming Unified Visual Representations for Native Unified Multimodal Models","created":"2025-12-01","cited_by_count":34,"area":null},{"id":"2503.10772","title":"FlowTok: Flowing Seamlessly Across Text and Image Tokens","created":"2025-03-13","cited_by_count":33,"area":null},{"id":"2605.18324","title":"Improved Baselines with Representation Autoencoders","created":"2026-05-18","cited_by_count":31,"area":null},{"id":"2509.14476","title":"AToken: A Unified Tokenizer for Vision","created":"2025-09-17","cited_by_count":30,"area":null},{"id":"2510.14974","title":"pi-Flow: Policy-Based Few-Step Generation via Imitation Distillation","created":"2025-10-16","cited_by_count":29,"area":null},{"id":"2503.08685","title":"\"Principal Components\" Enable A New Language of Images","created":"2025-03-11","cited_by_count":27,"area":null},{"id":"2503.18211","title":"SimMotionEdit: Text-Based Human Motion Editing with Motion Similarity Prediction","created":"2025-03-23","cited_by_count":27,"area":null},{"id":"2510.11712","title":"DiT360: High-Fidelity Panoramic Image Generation via Hybrid Training","created":"2025-10-13","cited_by_count":24,"area":null},{"id":"2501.15417","title":"AnyEnhance: A Unified Generative Model with Prompt-Guidance and Self-Critic for Voice Enhancement","created":"2025-01-26","cited_by_count":23,"area":null},{"id":"2503.01103","title":"Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator","created":"2025-03-03","cited_by_count":23,"area":null},{"id":"2510.10575","title":"UniFlow: A Unified Pixel Flow Tokenizer for Visual Understanding and Generation","created":"2025-10-12","cited_by_count":23,"area":null},{"id":"2507.08441","title":"Vision Foundation Models as Effective Visual Tokenizers for Autoregressive Image Generation","created":"2025-07-11","cited_by_count":21,"area":null},{"id":"2506.05289","title":"Towards Sequence Modeling Alignment between Tokenizer and Autoregressive Model","created":"2025-06-05","cited_by_count":20,"area":null},{"id":"2507.15856","title":"Latent Denoising Makes Good Tokenizers","created":"2025-07-21","cited_by_count":20,"area":null},{"id":"2509.14181","title":"Bridging Past and Future: Distribution-Aware Alignment for Time Series Forecasting","created":"2025-09-17","cited_by_count":20,"area":null},{"id":"2510.24474","title":"Decoupled MeanFlow: Turning Flow Models into Flow Maps for Accelerated Sampling","created":"2025-10-28","cited_by_count":20,"area":null},{"id":"2601.21406","title":"Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation","created":"2026-01-29","cited_by_count":20,"area":null},{"id":"2503.24026","title":"HumanDreamer: Generating Controllable Human-Motion Videos via Decoupled Generation","created":"2025-03-31","cited_by_count":19,"area":null},{"id":"2510.23588","title":"FARMER: Flow AutoRegressive Transformer over Pixels","created":"2025-10-27","cited_by_count":18,"area":null},{"id":"2604.24763","title":"Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation","created":"2026-04-27","cited_by_count":18,"area":null},{"id":"2503.19480","title":"GenHancer: Imperfect Generative Models are Secretly Strong Vision-Centric Enhancers","created":"2025-03-25","cited_by_count":16,"area":null},{"id":"2606.02572","title":"VISReg: Variance-Invariance-Sketching Regularization for JEPA training","created":"2026-06-01","cited_by_count":16,"area":null},{"id":"2503.15475","title":"Cube: A Roblox View of 3D Intelligence","created":"2025-03-19","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":"2505.18582","title":"On Denoising Walking Videos for Gait Recognition","created":"2025-05-24","cited_by_count":14,"area":null},{"id":"2506.07998","title":"Generative Modeling of Weights: Generalization or Memorization?","created":"2025-06-09","cited_by_count":14,"area":null},{"id":"2511.06876","title":"Generating an Image From 1,000 Words: Enhancing Text-to-Image With Structured Captions","created":"2025-11-10","cited_by_count":14,"area":null},{"id":"2511.19428","title":"Flow Map Distillation Without Data","created":"2025-11-24","cited_by_count":14,"area":null},{"id":"2512.03750","title":"Universally Converging Representations of Matter Across Scientific Foundation Models","created":"2025-12-03","cited_by_count":14,"area":null},{"id":"2601.02204","title":"NextFlow: Unified Sequential Modeling Activates Multimodal Understanding and Generation","created":"2026-01-05","cited_by_count":14,"area":null},{"id":"2504.20996","title":"X-Fusion: Introducing New Modality to Frozen Large Language Models","created":"2025-04-29","cited_by_count":13,"area":null},{"id":"2505.17778","title":"TextFlux: An OCR-Free DiT Model for High-Fidelity Multilingual Scene Text Synthesis","created":"2025-05-23","cited_by_count":13,"area":null},{"id":"2505.18142","title":"TokBench: Evaluating Your Visual Tokenizer before Visual Generation","created":"2025-05-23","cited_by_count":13,"area":null},{"id":"2510.14630","title":"Adapting Self-Supervised Representations as a Latent Space for Efficient Generation","created":"2025-10-16","cited_by_count":13,"area":null},{"id":"2412.01762","title":"XQ-GAN: An Open-source Image Tokenization Framework for Autoregressive Generation","created":"2024-12-02","cited_by_count":12,"area":null},{"id":"2511.22475","title":"Adversarial Flow Models","created":"2025-11-27","cited_by_count":12,"area":null},{"id":"2604.08503","title":"Phantom: Physics-Infused Video Generation via Joint Modeling of Visual and Latent Physical Dynamics","created":"2026-04-09","cited_by_count":12,"area":null},{"id":"2605.18678","title":"Lance: Unified Multimodal Modeling by Multi-Task Synergy","created":"2026-05-18","cited_by_count":12,"area":null},{"id":"2411.16681","title":"Factorized Visual Tokenization and Generation","created":"2024-11-25","cited_by_count":11,"area":null},{"id":"2504.11454","title":"Elucidating the Design Space of Multimodal Protein Language Models","created":"2025-04-15","cited_by_count":11,"area":null},{"id":"2506.17202","title":"UniFork: Exploring Modality Alignment for Unified Multimodal Understanding and Generation","created":"2025-06-20","cited_by_count":11,"area":null},{"id":"2604.04406","title":"3D-Fixer: Coarse-to-Fine In-place Completion for 3D Scenes from a Single Image","created":"2026-04-06","cited_by_count":11,"area":null},{"id":"2607.02375","title":"Representation Distribution Matching for One-Step Visual Generation","created":"2026-07-02","cited_by_count":11,"area":null},{"id":"2502.21318","title":"How far can we go with ImageNet for Text-to-Image generation?","created":"2025-02-28","cited_by_count":10,"area":null},{"id":"2504.05684","title":"TARO: Timestep-Adaptive Representation Alignment with Onset-Aware Conditioning for Synchronized Video-to-Audio Synthesis","created":"2025-04-08","cited_by_count":10,"area":null},{"id":"2511.23386","title":"VQRAE: Representation Quantization Autoencoders for Multimodal Understanding, Generation and Reconstruction","created":"2025-11-28","cited_by_count":10,"area":null},{"id":"2512.12193","title":"SMRABooth: Subject and Motion Representation Alignment for Customized Video Generation","created":"2025-12-13","cited_by_count":10,"area":null},{"id":"2602.18882","title":"SceneTok: A Compressed, Diffusable Token Space for 3D Scenes","created":"2026-02-21","cited_by_count":10,"area":null},{"id":"2603.25743","title":"RefAlign: Representation Alignment for Reference-to-Video Generation","created":"2026-03-26","cited_by_count":10,"area":null},{"id":"2503.14494","title":"Deeply Supervised Flow-Based Generative Models","created":"2025-03-18","cited_by_count":9,"area":null},{"id":"2504.12007","title":"Diffusion Generative Recommendation with Continuous Tokens","created":"2025-04-16","cited_by_count":9,"area":null},{"id":"2505.12387","title":"Neural Thermodynamics: Entropic Forces in Deep and Universal Representation Learning","created":"2025-05-18","cited_by_count":9,"area":null},{"id":"2505.23660","title":"D-AR: Diffusion via Autoregressive Models","created":"2025-05-29","cited_by_count":9,"area":null},{"id":"2506.18882","title":"Light of Normals: Unified Feature Representation for Universal Photometric Stereo","created":"2025-06-23","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":"2510.04910","title":"Glocal Information Bottleneck for Time Series Imputation","created":"2025-10-06","cited_by_count":9,"area":null},{"id":"2602.09024","title":"Autoregressive Image Generation with Masked Bit Modeling","created":"2026-02-09","cited_by_count":9,"area":null},{"id":"2412.00071","title":"COAP: Memory-Efficient Training with Correlation-Aware Gradient Projection","created":"2024-11-26","cited_by_count":8,"area":null},{"id":"2412.02690","title":"FoundHand: Large-Scale Domain-Specific Learning for Controllable Hand Image Generation","created":"2024-12-03","cited_by_count":8,"area":null},{"id":"2505.15197","title":"Intentional Gesture: Deliver Your Intentions with Gestures for Speech","created":"2025-05-21","cited_by_count":8,"area":null},{"id":"2509.23736","title":"HieraTok: Multi-Scale Visual Tokenizer Improves Image Reconstruction and Generation","created":"2025-09-28","cited_by_count":8,"area":null},{"id":"2603.19228","title":"SAMA: Factorized Semantic Anchoring and Motion Alignment for Instruction-Guided Video Editing","created":"2026-03-19","cited_by_count":8,"area":null},{"id":"2605.12964","title":"Asymmetric Flow Models","created":"2026-05-13","cited_by_count":8,"area":null},{"id":"2509.05441","title":"Decoupling High and Low Frequencies for Faithful Image Generation with Fine Details","created":"2025-09-05","cited_by_count":7,"area":null},{"id":"2509.15185","title":"Understand Before You Generate: Self-Guided Training for Autoregressive Image Generation","created":"2025-09-18","cited_by_count":7,"area":null},{"id":"2510.04961","title":"SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization","created":"2025-10-06","cited_by_count":7,"area":null},{"id":"2511.14063","title":"Semantic Context Matters: Improving Conditioning for Autoregressive Models","created":"2025-11-18","cited_by_count":7,"area":null},{"id":"2512.04084","title":"SimFlow: Simplified and End-to-End Training of Latent Normalizing Flows","created":"2025-12-03","cited_by_count":7,"area":null},{"id":"2512.10953","title":"Bidirectional Normalizing Flow: From Data to Noise and Back","created":"2025-12-11","cited_by_count":7,"area":null},{"id":"2603.12267","title":"EVATok: Adaptive Length Video Tokenization for Efficient Visual Autoregressive Generation","created":"2026-03-12","cited_by_count":7,"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":"2506.08456","title":"Improving Motion in Image-to-Video Models via Adaptive Low-Pass Guidance","created":"2025-06-10","cited_by_count":6,"area":null},{"id":"2510.21250","title":"Improved Training Technique for Shortcut Models","created":"2025-10-24","cited_by_count":6,"area":null},{"id":"2511.20565","title":"DINO-Tok: Adapting DINO for Visual Tokenizers","created":"2025-11-25","cited_by_count":6,"area":null},{"id":"2512.04483","title":"DeRA: Decoupled Representation Alignment for Video Tokenization","created":"2025-12-04","cited_by_count":6,"area":null},{"id":"2601.01535","title":"Improving Flexible Image Tokenizers for Autoregressive Image Generation","created":"2026-01-04","cited_by_count":6,"area":null},{"id":"2601.10632","title":"CoMoVi: Co-Generation of 3D Human Motions and Realistic Videos","created":"2026-01-15","cited_by_count":6,"area":null},{"id":"2602.00297","title":"From Observations to States: Latent Time Series Forecasting","created":"2026-01-30","cited_by_count":6,"area":null},{"id":"2602.06478","title":"Efficient-LVSM: Faster, Cheaper, and Better Large View Synthesis Model via Decoupled Co-Refinement Attention","created":"2026-02-06","cited_by_count":6,"area":null},{"id":"2604.12887","title":"VideoFlexTok: Flexible-Length Coarse-to-Fine Video Tokenization","created":"2026-04-14","cited_by_count":6,"area":null},{"id":"2605.21487","title":"Uni-Edit: Intelligent Editing Is A General Task For Unified Model Tuning","created":"2026-05-20","cited_by_count":6,"area":null},{"id":"2508.12811","title":"Next Visual Granularity Generation","created":"2025-08-18","cited_by_count":5,"area":null}],"next_cursor":"100"}