{"list":"other","total":110,"rows":[{"id":"1907.05600","title":"Generative Modeling by Estimating Gradients of the Data Distribution","created":"2019-07-12","cited_by_count":4101},{"id":"2308.06721","title":"IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models","created":"2023-08-13","cited_by_count":1464},{"id":"2508.10104","title":"DINOv3","created":"2025-08-13","cited_by_count":1414},{"id":"2502.09992","title":"Large Language Diffusion Models","created":"2025-02-14","cited_by_count":912},{"id":"2410.18072","title":"WorldSimBench: Towards Video Generation Models as World Simulators","created":"2024-10-23","cited_by_count":881},{"id":"2501.03575","title":"Cosmos World Foundation Model Platform for Physical AI","created":"2025-01-07","cited_by_count":864},{"id":"2409.18869","title":"Emu3: Next-Token Prediction is All You Need","created":"2024-09-27","cited_by_count":781},{"id":"2508.15487","title":"Dream 7B: Diffusion Large Language Models","created":"2025-08-21","cited_by_count":544},{"id":"2404.08471","title":"Revisiting Feature Prediction for Learning Visual Representations from Video","created":"2024-02-15","cited_by_count":531},{"id":"2302.03027","title":"Zero-shot Image-to-Image Translation","created":"2023-02-06","cited_by_count":505},{"id":"2504.17761","title":"Step1X-Edit: A Practical Framework for General Image Editing","created":"2025-04-24","cited_by_count":429},{"id":"2505.09568","title":"BLIP3-o: A Family of Fully Open Unified Multimodal Models-Architecture, Training and Dataset","created":"2025-05-14","cited_by_count":376},{"id":"2404.14396","title":"SEED-X: Multimodal Models with Unified Multi-granularity Comprehension and Generation","created":"2024-04-22","cited_by_count":331},{"id":"2405.12399","title":"Diffusion for World Modeling: Visual Details Matter in Atari","created":"2024-05-20","cited_by_count":300},{"id":"1711.04340","title":"Data Augmentation Generative Adversarial Networks","created":"2017-11-12","cited_by_count":278},{"id":"2506.18871","title":"OmniGen2: Towards Instruction-Aligned Multimodal Generation","created":"2025-06-23","cited_by_count":253},{"id":"2505.15809","title":"MMaDA: Multimodal Large Diffusion Language Models","created":"2025-05-21","cited_by_count":250},{"id":"2210.04885","title":"What the DAAM: Interpreting Stable Diffusion Using Cross Attention","created":"2022-10-10","cited_by_count":236},{"id":"2305.10973","title":"Drag Your GAN: Interactive Point-based Manipulation on the Generative Image Manifold","created":"2023-05-18","cited_by_count":219},{"id":"2504.20690","title":"In-Context Edit: Enabling Instructional Image Editing with In-Context Generation in Large Scale Diffusion Transformer","created":"2025-04-29","cited_by_count":204},{"id":"2305.20030","title":"Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust","created":"2023-05-31","cited_by_count":187},{"id":"2306.00984","title":"StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners","created":"2023-06-01","cited_by_count":177},{"id":"2307.08041","title":"Planting a SEED of Vision in Large Language Model","created":"2023-07-16","cited_by_count":140},{"id":"2306.01953","title":"Invisible Image Watermarks Are Provably Removable Using Generative AI","created":"2023-06-02","cited_by_count":134},{"id":"2412.15188","title":"LMFusion: Adapting Pretrained Language Models for Multimodal Generation","created":"2024-12-19","cited_by_count":120},{"id":"2309.14303","title":"Dataset Diffusion: Diffusion-based Synthetic Dataset Generation for Pixel-Level Semantic Segmentation","created":"2023-09-25","cited_by_count":112},{"id":"2507.22058","title":"X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again","created":"2025-07-29","cited_by_count":112},{"id":"2505.05472","title":"Mogao: An Omni Foundation Model for Interleaved Multi-Modal Generation","created":"2025-05-08","cited_by_count":109},{"id":"2505.16990","title":"Dimple: Discrete Diffusion Multimodal Large Language Model with Parallel Decoding","created":"2025-05-22","cited_by_count":101},{"id":"2305.16289","title":"Diversify Your Vision Datasets with Automatic Diffusion-Based Augmentation","created":"2023-05-25","cited_by_count":100},{"id":"2312.03701","title":"Return of Unconditional Generation: A Self-supervised Representation Generation Method","created":"2023-12-06","cited_by_count":98},{"id":"2505.23656","title":"VideoREPA: Learning Physics for Video Generation through Relational Alignment with Foundation Models","created":"2025-05-29","cited_by_count":98},{"id":"2305.12683","title":"Mist: Towards Improved Adversarial Examples for Diffusion Models","created":"2023-05-22","cited_by_count":94},{"id":"1803.09655","title":"BAGAN: Data Augmentation with Balancing GAN","created":"2018-03-26","cited_by_count":90},{"id":"2401.10208","title":"MM-Interleaved: Interleaved Image-Text Generative Modeling via Multi-modal Feature Synchronizer","created":"2024-01-18","cited_by_count":80},{"id":"2405.20337","title":"OccSora: 4D Occupancy Generation Models as World Simulators for Autonomous Driving","created":"2024-05-30","cited_by_count":78},{"id":"2404.02928","title":"Jailbreaking Prompt Attack: A Controllable Adversarial Attack against Diffusion Models","created":"2024-04-02","cited_by_count":72},{"id":"2505.19017","title":"WorldEval: World Model as Real-World Robot Policies Evaluator","created":"2025-05-25","cited_by_count":68},{"id":"2305.08694","title":"A Reproducible Extraction of Training Images from Diffusion Models","created":"2023-05-15","cited_by_count":61},{"id":"2310.15160","title":"FreeMask: Synthetic Images with Dense Annotations Make Stronger Segmentation Models","created":"2023-10-23","cited_by_count":61},{"id":"2307.12698","title":"MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features","created":"2023-07-24","cited_by_count":57},{"id":"2505.14671","title":"UniCTokens: Boosting Personalized Understanding and Generation via Unified Concept Tokens","created":"2025-05-20","cited_by_count":56},{"id":"2305.15779","title":"Custom-Edit: Text-Guided Image Editing with Customized Diffusion Models","created":"2023-05-25","cited_by_count":54},{"id":"2503.13436","title":"Unified Autoregressive Visual Generation and Understanding with Continuous Tokens","created":"2025-03-17","cited_by_count":51},{"id":"2505.20147","title":"FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities","created":"2025-05-26","cited_by_count":46},{"id":"2604.14268","title":"HY-World 2.0: A Multi-Modal World Model for Reconstructing, Generating, and Simulating 3D Worlds","created":"2026-04-15","cited_by_count":44},{"id":"2210.09477","title":"UniTune: Text-Driven Image Editing by Fine Tuning a Diffusion Model on a Single Image","created":"2022-10-17","cited_by_count":42},{"id":"2509.04548","title":"Skywork UniPic 2.0: Building Kontext Model with Online RL for Unified Multimodal Model","created":"2025-09-04","cited_by_count":41},{"id":"2212.09541","title":"Positive-incentive Noise","created":"2022-12-19","cited_by_count":39},{"id":"2306.07651","title":"Variational Positive-incentive Noise: How Noise Benefits Models","created":"2023-06-13","cited_by_count":38},{"id":"2505.09608","title":"LightLab: Controlling Light Sources in Images with Diffusion Models","created":"2025-05-14","cited_by_count":38},{"id":"2309.13042","title":"MosaicFusion: Diffusion Models as Data Augmenters for Large Vocabulary Instance Segmentation","created":"2023-09-22","cited_by_count":35},{"id":"2412.10817","title":"Enhance Vision-Language Alignment with Noise","created":"2024-12-14","cited_by_count":34},{"id":"2412.01407","title":"HoloDrive: Holistic 2D-3D Multi-Modal Street Scene Generation for Autonomous Driving","created":"2024-12-02","cited_by_count":23},{"id":"2503.08250","title":"Aligning Text to Image in Diffusion Models is Easier Than You Think","created":"2025-03-11","cited_by_count":22},{"id":"2510.13721","title":"NExT-OMNI: Towards Any-to-Any Omnimodal Foundation Models with Discrete Flow Matching","created":"2025-10-15","cited_by_count":21},{"id":"2405.20282","title":"SemFlow: Binding Semantic Segmentation and Image Synthesis via Rectified Flow","created":"2024-05-30","cited_by_count":20},{"id":"2506.13558","title":"X-Scene: Large-Scale Driving Scene Generation with High Fidelity and Flexible Controllability","created":"2025-06-16","cited_by_count":20},{"id":"2303.05105","title":"MaskDiff: Modeling Mask Distribution with Diffusion Probabilistic Model for Few-Shot Instance Segmentation","created":"2023-03-09","cited_by_count":18},{"id":"2206.09592","title":"DALL-E for Detection: Language-driven Compositional Image Synthesis for Object Detection","created":"2022-06-20","cited_by_count":17},{"id":"2412.02366","title":"GenMix: Effective Data Augmentation with Generative Diffusion Model Image Editing","created":"2024-12-03","cited_by_count":14},{"id":"2506.13260","title":"COME: Adding Scene-Centric Forecasting Control to Occupancy World Model","created":"2025-06-16","cited_by_count":14},{"id":"2509.16738","title":"Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learning","created":"2025-09-20","cited_by_count":14},{"id":"2501.04969","title":"Self-Supervised Representation Learning with Joint Embedding Predictive Architecture for Automotive LiDAR Object Detection","created":"2025-01-09","cited_by_count":13},{"id":"2510.14630","title":"Adapting Self-Supervised Representations as a Latent Space for Efficient Generation","created":"2025-10-16","cited_by_count":13},{"id":"2604.20796","title":"LLaDA2.0-Uni: Unifying Multimodal Understanding and Generation with Diffusion Large Language Model","created":"2026-04-22","cited_by_count":13},{"id":"2604.22152","title":"dWorldEval: Scalable Robotic Policy Evaluation via Discrete Diffusion World Model","created":"2026-04-24","cited_by_count":13},{"id":"2403.09616","title":"Explore In-Context Segmentation via Latent Diffusion Models","created":"2024-03-14","cited_by_count":12},{"id":"2308.05695","title":"Masked Diffusion as Self-supervised Representation Learner","created":"2023-08-10","cited_by_count":11},{"id":"2511.12917","title":"Explore How to Inject Beneficial Noise in MLLMs","created":"2025-11-17","cited_by_count":10},{"id":"2510.22946","title":"LightFusion: A Light-weighted, Double Fusion Framework for Unified Multimodal Understanding and Generation","created":"2025-10-27","cited_by_count":9},{"id":"2511.18262","title":"MammothModa2: A Unified AR-Diffusion Framework for Multimodal Understanding and Generation","created":"2025-11-23","cited_by_count":9},{"id":"2310.07726","title":"Warfare:Breaking the Watermark Protection of AI-Generated Content","created":"2023-09-27","cited_by_count":8},{"id":"2505.18766","title":"StyleGuard: Preventing Text-to-Image-Model-based Style Mimicry Attacks by Style Perturbations","created":"2025-05-24","cited_by_count":8},{"id":"2506.10634","title":"Symmetrical Flow Matching: Unified Image Generation, Segmentation, and Classification with Score-Based Generative Models","created":"2025-06-12","cited_by_count":8},{"id":"2506.14549","title":"DreamLight: Towards Harmonious and Consistent Image Relighting","created":"2025-06-17","cited_by_count":8},{"id":"2603.10422","title":"World2Act: Latent Action Post-Training from World Model Dynamics","created":"2026-03-11","cited_by_count":8},{"id":"2511.07911","title":"Rectified Noise: A Generative Model Using Positive-incentive Noise","created":"2025-11-11","cited_by_count":7},{"id":"2512.16625","title":"DeContext as Defense: Safe Image Editing in Diffusion Transformers","created":"2025-12-18","cited_by_count":7},{"id":"2503.05595","title":"Anti-Diffusion: Preventing Abuse of Modifications of Diffusion-Based Models","created":"2025-03-07","cited_by_count":6},{"id":"2505.04486","title":"Efficient Flow Matching using Latent Variables","created":"2025-05-07","cited_by_count":6},{"id":"2510.15783","title":"ReCon: Region-Controllable Data Augmentation with Rectification and Alignment for Object Detection","created":"2025-10-17","cited_by_count":6},{"id":"2511.07934","title":"Laytrol: Preserving Pretrained Knowledge in Layout Control for Multimodal Diffusion Transformers","created":"2025-11-11","cited_by_count":6},{"id":"2311.17121","title":"ScribbleGen: Generative Data Augmentation Improves Scribble-supervised Semantic Segmentation","created":"2023-11-28","cited_by_count":5},{"id":"2503.03944","title":"GuardDoor: Safeguarding Against Malicious Diffusion Editing via Protective Backdoors","created":"2025-03-05","cited_by_count":5},{"id":"2509.10569","title":"MarkDiffusion: An Open-Source Toolkit for Generative Watermarking of Latent Diffusion Models","created":"2025-09-11","cited_by_count":5},{"id":"2301.12247","title":"SEGA: Instructing Text-to-Image Models using Semantic Guidance","created":"2023-01-28","cited_by_count":4},{"id":"2604.12273","title":"SubFlow: Sub-mode Conditioned Flow Matching for Diverse One-Step Generation","created":"2026-04-14","cited_by_count":4},{"id":"2505.13023","title":"Anti-Inpainting: A Proactive Defense Approach against Malicious Diffusion-based Inpainters under Unknown Conditions","created":"2025-05-19","cited_by_count":3},{"id":"2507.03953","title":"Evaluating Adversarial Protections for Diffusion Personalization: A Comprehensive Study","created":"2025-07-05","cited_by_count":3},{"id":"2509.15553","title":"Diffusion-Based Cross-Modal Feature Extraction for Multi-Label Classification","created":"2025-09-19","cited_by_count":3},{"id":"2501.02048","title":"DreamMask: Boosting Open-vocabulary Panoptic Segmentation with Synthetic Data","created":"2025-01-03","cited_by_count":2},{"id":"2602.20680","title":"Vanishing Watermarks: Diffusion-Based Image Editing Undermines Robust Invisible Watermarking","created":"2026-02-24","cited_by_count":2},{"id":"2603.13928","title":"Discriminative Flow Matching Via Local Generative Predictors","created":"2026-03-14","cited_by_count":2},{"id":"2604.19090","title":"Dual-Guard: Dual-Channel Latent Watermarking for Provenance and Tamper Localization in Diffusion Images","created":"2026-04-21","cited_by_count":2},{"id":"2502.04475","title":"Augmented Conditioning Is Enough For Effective Training Image Generation","created":"2025-02-06","cited_by_count":1},{"id":"2504.03850","title":"Detection Limits and Statistical Separability of Tree Ring Watermarks in Rectified Flow-based Text-to-Image Generation Models","created":"2025-04-04","cited_by_count":1},{"id":"2510.23015","title":"Coupled Flow Matching","created":"2025-10-27","cited_by_count":1},{"id":"2512.15769","title":"Data-Chain Backdoor: Do You Trust Diffusion Models as Generative Data Supplier?","created":"2025-12-12","cited_by_count":1},{"id":"2601.15049","title":"Deep Leakage with Generative Flow Matching Denoiser","created":"2026-01-21","cited_by_count":1}],"next_cursor":"100"}