{"total":165,"rows":[{"id":"2508.02324","title":"Qwen-Image Technical Report","created":"2025-08-04","cited_by_count":1044,"area":null},{"id":"2505.05470","title":"Flow-GRPO: Training Flow Matching Models via Online RL","created":"2025-05-08","cited_by_count":661,"area":"lr"},{"id":"2503.09567","title":"Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models","created":"2025-03-12","cited_by_count":384,"area":"lr"},{"id":"2502.12524","title":"YOLOv12: Attention-Centric Real-Time Object Detectors","created":"2025-02-18","cited_by_count":305,"area":null},{"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,"area":"diffusion"},{"id":"2505.18875","title":"Sparse VideoGen2: Accelerate Video Generation with Sparse Attention via Semantic-Aware Permutation","created":"2025-05-24","cited_by_count":106,"area":"diffusion"},{"id":"2508.04324","title":"TempFlow-GRPO: When Timing Matters for GRPO in Flow Models","created":"2025-08-06","cited_by_count":97,"area":"lr"},{"id":"2503.21758","title":"Lumina-Image 2.0: A Unified and Efficient Image Generative Framework","created":"2025-03-27","cited_by_count":96,"area":null},{"id":"2509.24695","title":"SANA-Video: Efficient Video Generation with Block Linear Diffusion Transformer","created":"2025-09-29","cited_by_count":94,"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":"2503.09641","title":"SANA-Sprint: One-Step Diffusion with Continuous-Time Consistency Distillation","created":"2025-03-12","cited_by_count":87,"area":"diffusion"},{"id":"2510.08431","title":"Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency","created":"2025-10-09","cited_by_count":86,"area":"diffusion"},{"id":"2506.02161","title":"TIIF-Bench: How Does Your T2I Model Follow Your Instructions?","created":"2025-06-02","cited_by_count":69,"area":null},{"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":"2504.16080","title":"From Reflection to Perfection: Scaling Inference-Time Optimization for Text-to-Image Diffusion Models via Reflection Tuning","created":"2025-04-22","cited_by_count":56,"area":"diffusion"},{"id":"2601.16208","title":"Scaling Text-to-Image Diffusion Transformers with Representation Autoencoders","created":"2026-01-22","cited_by_count":53,"area":"diffusion"},{"id":"2505.23614","title":"Inference-time Scaling of Diffusion Models through Classical Search","created":"2025-05-29","cited_by_count":49,"area":"lr"},{"id":"2509.07295","title":"Reconstruction Alignment Improves Unified Multimodal Models","created":"2025-09-08","cited_by_count":49,"area":null},{"id":"2508.00413","title":"DC-AE 1.5: Accelerating Diffusion Model Convergence with Structured Latent Space","created":"2025-08-01","cited_by_count":47,"area":"diffusion"},{"id":"2505.20147","title":"FUDOKI: Discrete Flow-based Unified Understanding and Generation via Kinetic-Optimal Velocities","created":"2025-05-26","cited_by_count":46,"area":"mllm"},{"id":"2505.23661","title":"OpenUni: A Simple Baseline for Unified Multimodal Understanding and Generation","created":"2025-05-29","cited_by_count":46,"area":null},{"id":"2503.12271","title":"Reflect-DiT: Inference-Time Scaling for Text-to-Image Diffusion Transformers via In-Context Reflection","created":"2025-03-15","cited_by_count":43,"area":"lr"},{"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,"area":null},{"id":"2509.06945","title":"Interleaving Reasoning for Better Text-to-Image Generation","created":"2025-09-08","cited_by_count":41,"area":null},{"id":"2505.17618","title":"Scaling Image and Video Generation via Test-Time Evolutionary Search","created":"2025-05-23","cited_by_count":40,"area":"lr"},{"id":"2503.19385","title":"Inference-Time Scaling for Flow Models via Stochastic Generation and Rollover Budget Forcing","created":"2025-03-25","cited_by_count":38,"area":"lr"},{"id":"2509.09680","title":"FLUX-Reason-6M & PRISM-Bench: A Million-Scale Text-to-Image Reasoning Dataset and Comprehensive Benchmark","created":"2025-09-11","cited_by_count":38,"area":"lr"},{"id":"2505.16792","title":"REPA Works Until It Doesn't: Early-Stopped, Holistic Alignment Supercharges Diffusion Training","created":"2025-05-22","cited_by_count":37,"area":"diffusion"},{"id":"2507.17801","title":"Lumina-mGPT 2.0: Stand-Alone AutoRegressive Image Modeling","created":"2025-07-23","cited_by_count":37,"area":null},{"id":"2603.03276","title":"Beyond Language Modeling: An Exploration of Multimodal Pretraining","created":"2026-03-03","cited_by_count":37,"area":"moe"},{"id":"2509.04394","title":"Transition Models: Rethinking the Generative Learning Objective","created":"2025-09-04","cited_by_count":34,"area":"diffusion"},{"id":"2505.14682","title":"UniGen: Enhanced Training & Test-Time Strategies for Unified Multimodal Understanding and Generation","created":"2025-05-20","cited_by_count":32,"area":"mllm"},{"id":"2505.23493","title":"R2I-Bench: Benchmarking Reasoning-Driven Text-to-Image Generation","created":"2025-05-29","cited_by_count":32,"area":null},{"id":"2505.13031","title":"MindOmni: Unleashing Reasoning Generation in Vision Language Models with RGPO","created":"2025-05-19","cited_by_count":30,"area":"lr"},{"id":"2504.13143","title":"$\\texttt{Complex-Edit}$: CoT-Like Instruction Generation for Complexity-Controllable Image Editing Benchmark","created":"2025-04-17","cited_by_count":27,"area":null},{"id":"2505.17941","title":"VeriThinker: Learning to Verify Makes Reasoning Model Efficient","created":"2025-05-23","cited_by_count":24,"area":"lr"},{"id":"2505.17540","title":"RePrompt: Reasoning-Augmented Reprompting for Text-to-Image Generation via Reinforcement Learning","created":"2025-05-23","cited_by_count":23,"area":"lr"},{"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":"2512.21675","title":"UniPercept: Towards Unified Perceptual-Level Image Understanding across Aesthetics, Quality, Structure, and Texture","created":"2025-12-25","cited_by_count":22,"area":"mllm"},{"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,"area":"diffusion"},{"id":"2510.05091","title":"Factuality Matters: When Image Generation and Editing Meet Structured Visuals","created":"2025-10-06","cited_by_count":20,"area":"lr"},{"id":"2505.02665","title":"A Survey of Slow Thinking-based Reasoning LLMs using Reinforced Learning and Inference-time Scaling Law","created":"2025-05-05","cited_by_count":19,"area":"lr"},{"id":"2511.11483","title":"ImAgent: A Unified Multimodal Agent Framework for Test-Time Scalable Image Generation","created":"2025-11-14","cited_by_count":17,"area":null},{"id":"2512.05150","title":"TwinFlow: Realizing One-step Generation on Large Models with Self-adversarial Flows","created":"2025-12-03","cited_by_count":17,"area":null},{"id":"2512.24138","title":"GARDO: Reinforcing Diffusion Models without Reward Hacking","created":"2025-12-30","cited_by_count":17,"area":"diffusion"},{"id":"2505.10046","title":"Exploring the Deep Fusion of Large Language Models and Diffusion Transformers for Text-to-Image Synthesis","created":"2025-05-15","cited_by_count":16,"area":"diffusion"},{"id":"2601.20354","title":"Everything in Its Place: Benchmarking Spatial Intelligence of Text-to-Image Models","created":"2026-01-28","cited_by_count":16,"area":null},{"id":"2507.18537","title":"TTS-VAR: A Test-Time Scaling Framework for Visual Auto-Regressive Generation","created":"2025-07-24","cited_by_count":15,"area":"lr"},{"id":"2509.19244","title":"Lavida-O: Elastic Large Masked Diffusion Models for Unified Multimodal Understanding and Generation","created":"2025-09-23","cited_by_count":15,"area":"diffusion"},{"id":"2509.25027","title":"STAGE: Stable and Generalizable GRPO for Autoregressive Image Generation","created":"2025-09-29","cited_by_count":15,"area":"lr"},{"id":"2510.08425","title":"Reinforcing Diffusion Models by Direct Group Preference Optimization","created":"2025-10-09","cited_by_count":14,"area":"lr"},{"id":"2510.20888","title":"Video-As-Prompt: Unified Semantic Control for Video Generation","created":"2025-10-23","cited_by_count":14,"area":null},{"id":"2505.21179","title":"Normalized Attention Guidance: Universal Negative Guidance for Diffusion Models","created":"2025-05-27","cited_by_count":13,"area":"diffusion"},{"id":"2507.04947","title":"DC-AR: Efficient Masked Autoregressive Image Generation with Deep Compression Hybrid Tokenizer","created":"2025-07-07","cited_by_count":13,"area":null},{"id":"2508.00697","title":"On-Device Diffusion Transformer Policy for Efficient Robot Manipulation","created":"2025-08-01","cited_by_count":13,"area":"diffusion"},{"id":"2503.16400","title":"ScalingNoise: Scaling Inference-Time Search for Generating Infinite Videos","created":"2025-03-20","cited_by_count":12,"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":"2604.21221","title":"Sparse Forcing: Native Trainable Sparse Attention for Real-time Autoregressive Diffusion Video Generation","created":"2026-04-23","cited_by_count":11,"area":"diffusion"},{"id":"2605.30409","title":"SANA-Streaming: Real-time Streaming Video Editing with Hybrid Diffusion Transformer","created":"2026-05-28","cited_by_count":11,"area":"diffusion"},{"id":"2503.21082","title":"Can Video Diffusion Model Reconstruct 4D Geometry?","created":"2025-03-27","cited_by_count":10,"area":"diffusion"},{"id":"2507.08422","title":"Training-free Mixed-Resolution Latent Upsampling for Spatially Accelerated Diffusion Transformers","created":"2025-07-11","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":"2510.20206","title":"RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling","created":"2025-10-23","cited_by_count":10,"area":"lr"},{"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":"2506.01480","title":"Janus-Pro-R1: Advancing Collaborative Visual Comprehension and Generation via Reinforcement Learning","created":"2025-06-02","cited_by_count":9,"area":"mllm"},{"id":"2507.13343","title":"Taming Diffusion Transformer for Efficient Mobile Video Generation in Seconds","created":"2025-07-17","cited_by_count":9,"area":"diffusion"},{"id":"2510.14847","title":"ImagerySearch: Adaptive Test-Time Search for Video Generation Beyond Semantic Dependency Constraints","created":"2025-10-16","cited_by_count":9,"area":null},{"id":"2503.16726","title":"EDiT: Efficient Diffusion Transformers with Linear Compressed Attention","created":"2025-03-20","cited_by_count":8,"area":"diffusion"},{"id":"2509.25127","title":"Score Distillation of Flow Matching Models","created":"2025-09-29","cited_by_count":8,"area":"diffusion"},{"id":"2509.25180","title":"DC-Gen: Post-Training Diffusion Acceleration with Deeply Compressed Latent Space","created":"2025-09-29","cited_by_count":8,"area":"diffusion"},{"id":"2512.04810","title":"EMMA: Efficient Multimodal Understanding, Generation, and Editing with a Unified Architecture","created":"2025-12-04","cited_by_count":8,"area":null},{"id":"2603.00141","title":"From Scale to Speed: Adaptive Test-Time Scaling for Image Editing","created":"2026-02-24","cited_by_count":8,"area":"lr"},{"id":"2605.26108","title":"Reinforcing Few-step Generators via Reward-Tilted Distribution Matching","created":"2026-05-25","cited_by_count":8,"area":"diffusion"},{"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":"2510.08123","title":"High-dimensional Analysis of Synthetic Data Selection","created":"2025-10-09","cited_by_count":7,"area":null},{"id":"2603.00483","title":"RAISE: Requirement-Adaptive Evolutionary Refinement for Training-Free Text-to-Image Alignment","created":"2026-02-28","cited_by_count":7,"area":"diffusion"},{"id":"2603.07700","title":"TDM-R1: Reinforcing Few-Step Diffusion Models with Non-Differentiable Reward","created":"2026-03-08","cited_by_count":7,"area":"diffusion"},{"id":"2510.07217","title":"GenPilot: A Multi-Agent System for Test-Time Prompt Optimization in Image Generation","created":"2025-10-08","cited_by_count":6,"area":null},{"id":"2510.18053","title":"Adaptive Divergence Regularized Policy Optimization for Fine-tuning Generative Models","created":"2025-10-20","cited_by_count":6,"area":"alignment"},{"id":"2603.22125","title":"DA-VAE: Plug-in Latent Compression for Diffusion via Detail Alignment","created":"2026-03-23","cited_by_count":6,"area":"diffusion"},{"id":"2506.01331","title":"Ultra-High-Resolution Image Synthesis: Data, Method and Evaluation","created":"2025-06-02","cited_by_count":5,"area":"diffusion"},{"id":"2604.12163","title":"Nucleus-Image: Sparse MoE for Image Generation","created":"2026-04-14","cited_by_count":5,"area":"diffusion"},{"id":"2606.01803","title":"OctoT2I: A Self-Evolving Agentic Text-to-Image Router","created":"2026-06-01","cited_by_count":5,"area":"agents"},{"id":"2508.10511","title":"KDPE: A Kernel Density Estimation Strategy for Diffusion Policy Trajectory Selection","created":"2025-08-14","cited_by_count":4,"area":"diffusion"},{"id":"2509.01986","title":"Draw-In-Mind: Rebalancing Designer-Painter Roles in Unified Multimodal Models Benefits Image Editing","created":"2025-09-02","cited_by_count":4,"area":null},{"id":"2510.01546","title":"Growing Visual Generative Capacity for Pre-Trained MLLMs","created":"2025-10-02","cited_by_count":4,"area":"mllm"},{"id":"2512.08505","title":"Early Estimation of Language to Latent Alignment in Diffusion Models","created":"2025-12-09","cited_by_count":4,"area":"diffusion"},{"id":"2602.01591","title":"Faster and Better Alignment for Flow Matching Models via Step-aware Advantages","created":"2026-02-02","cited_by_count":4,"area":"diffusion"},{"id":"2602.14041","title":"BitDance: Scaling Autoregressive Generative Models with Binary Tokens","created":"2026-02-15","cited_by_count":4,"area":null},{"id":"2603.22492","title":"Tiny Inference-Time Scaling with Latent Verifiers","created":"2026-03-23","cited_by_count":4,"area":"lr"},{"id":"2606.03183","title":"Inference-Time Scaling for Joint Audio-Video Generation","created":"2026-06-02","cited_by_count":4,"area":"lr"},{"id":"2508.02391","title":"Inference-time Scaling for Diffusion-based Audio Super-resolution","created":"2025-08-04","cited_by_count":3,"area":"diffusion"},{"id":"2510.16325","title":"UltraImageGen: Efficient Ultra-High-Resolution Image Generation with Hierarchical Local Attention","created":"2025-10-18","cited_by_count":3,"area":"diffusion"},{"id":"2511.08930","title":"From Structure to Detail: Hierarchical Distillation for Efficient Diffusion Model","created":"2025-11-12","cited_by_count":3,"area":"diffusion"},{"id":"2512.01302","title":"DCText: Scheduled Attention Masking for Visual Text Generation via Divide-and-Conquer Strategy","created":"2025-12-01","cited_by_count":3,"area":null},{"id":"2512.22374","title":"Self-Evaluation Unlocks Any-Step Text-to-Image Generation","created":"2025-12-26","cited_by_count":3,"area":"diffusion"},{"id":"2601.05149","title":"Multi-Scale Local Speculative Decoding for Image Generation","created":"2026-01-08","cited_by_count":3,"area":"inference"},{"id":"2601.19506","title":"Bridging Information Asymmetry: A Hierarchical Framework for Deterministic Blind Face Restoration","created":"2026-01-27","cited_by_count":3,"area":null},{"id":"2603.00180","title":"NNiT: Width-Agnostic Neural Network Generation with Structurally Aligned Weight Spaces","created":"2026-02-26","cited_by_count":3,"area":null},{"id":"2604.02289","title":"Omni123: Exploring 3D Native Foundation Models with Limited 3D Data by Unifying Text to 2D and 3D Generation","created":"2026-04-02","cited_by_count":3,"area":"mllm"}],"next_cursor":"100"}