{"total":87,"rows":[{"id":"2508.02324","title":"Qwen-Image Technical Report","created":"2025-08-04","cited_by_count":1044,"area":null},{"id":"2511.22699","title":"Z-Image: An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer","created":"2025-11-27","cited_by_count":277,"area":"diffusion"},{"id":"2506.18871","title":"OmniGen2: Towards Instruction-Aligned Multimodal Generation","created":"2025-06-23","cited_by_count":253,"area":null},{"id":"2506.15564","title":"Show-o2: Improved Native Unified Multimodal Models","created":"2025-06-18","cited_by_count":250,"area":"diffusion"},{"id":"2510.26583","title":"Emu3.5: Native Multimodal Models are World Learners","created":"2025-10-30","cited_by_count":132,"area":"wm"},{"id":"2507.22058","title":"X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again","created":"2025-07-29","cited_by_count":112,"area":"deeprl"},{"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":"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":"2512.16853","title":"GenEval 2: Addressing Benchmark Drift in Text-to-Image Evaluation","created":"2025-12-18","cited_by_count":52,"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":"2509.03516","title":"Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?","created":"2025-09-03","cited_by_count":34,"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":"2605.12500","title":"SenseNova-U1: Unifying Multimodal Understanding and Generation with NEO-unify Architecture","created":"2026-05-12","cited_by_count":32,"area":"mllm"},{"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":"2603.09877","title":"InternVL-U: Democratizing Unified Multimodal Models for Understanding, Reasoning, Generation and Editing","created":"2026-03-10","cited_by_count":28,"area":"lr"},{"id":"2601.03193","title":"UniCorn: Towards Self-Improving Unified Multimodal Models through Self-Generated Supervision","created":"2026-01-06","cited_by_count":26,"area":null},{"id":"2509.14232","title":"GenExam: A Multidisciplinary Text-to-Image Exam","created":"2025-09-17","cited_by_count":22,"area":null},{"id":"2605.28091","title":"Qwen-Image-Bench: From Generation to Creation in Text-to-Image Evaluation","created":"2026-05-27","cited_by_count":22,"area":null},{"id":"2603.28088","title":"GEMS: Agent-Native Multimodal Generation with Memory and Skills","created":"2026-03-30","cited_by_count":21,"area":null},{"id":"2512.16899","title":"Multimodal RewardBench 2: Evaluating Omni Reward Models for Interleaved Text and Image","created":"2025-12-18","cited_by_count":20,"area":"alignment"},{"id":"2601.04498","title":"IGenBench: Benchmarking the Reliability of Text-to-Infographic Generation","created":"2026-01-08","cited_by_count":17,"area":null},{"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":"2602.20903","title":"TextPecker: Rewarding Structural Anomaly Quantification for Enhancing Visual Text Rendering","created":"2026-02-24","cited_by_count":15,"area":null},{"id":"2603.07244","title":"PresentBench: A Fine-Grained Rubric-Based Benchmark for Slide Generation","created":"2026-03-07","cited_by_count":14,"area":null},{"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,"area":"diffusion"},{"id":"2605.04128","title":"JoyAI-Image: Awaking Spatial Intelligence in Unified Multimodal Understanding and Generation","created":"2026-05-05","cited_by_count":12,"area":null},{"id":"2603.25732","title":"BizGenEval: A Systematic Benchmark for Commercial Visual Content Generation","created":"2026-03-26","cited_by_count":11,"area":null},{"id":"2607.26004","title":"Parallel Decoding Distillation for Fast Image and Video Generation","created":"2026-07-28","cited_by_count":10,"area":"diffusion"},{"id":"2507.15085","title":"OCRGenBench: A Comprehensive Benchmark for Evaluating OCR Generative Capabilities","created":"2025-07-20","cited_by_count":9,"area":null},{"id":"2511.22982","title":"Ovis-Image Technical Report","created":"2025-11-28","cited_by_count":8,"area":null},{"id":"2602.12279","title":"UniT: Unified Multimodal Chain-of-Thought Test-time Scaling","created":"2026-02-12","cited_by_count":8,"area":"lr"},{"id":"2511.16156","title":"Pluggable Pruning with Contiguous Layer Distillation for Diffusion Transformers","created":"2025-11-20","cited_by_count":7,"area":"diffusion"},{"id":"2602.08336","title":"UReason: Benchmarking Reasoning-to-Generation Alignment in Unified Multimodal Models","created":"2026-02-09","cited_by_count":7,"area":null},{"id":"2609.11929","title":"SenseNova-U1.5: Towards Native Unified Visual Intelligence","created":"2026-09-10","cited_by_count":7,"area":"distill"},{"id":"2602.06166","title":"M3: High-fidelity Text-to-Image Generation via Multi-Modal, Multi-Agent and Multi-Round Visual Reasoning","created":"2026-02-05","cited_by_count":6,"area":"lr"},{"id":"2603.08652","title":"CoCo: Code as CoT for Text-to-Image Preview and Rare Concept Generation","created":"2026-03-09","cited_by_count":6,"area":"lr"},{"id":"2603.15616","title":"GlyphPrinter: Region-Grouped Direct Preference Optimization for Glyph-Accurate Visual Text Rendering","created":"2026-03-16","cited_by_count":6,"area":"alignment"},{"id":"2605.21573","title":"Lens: Rethinking Training Efficiency for Foundational Text-to-Image Models","created":"2026-05-20","cited_by_count":6,"area":null},{"id":"2605.25347","title":"ERNIE-Image Technical Report","created":"2026-05-25","cited_by_count":6,"area":null},{"id":"2607.01709","title":"COMFYCLAW: Self-Evolving Skill Harnesses for Image Generation Workflows","created":"2026-07-02","cited_by_count":6,"area":"synth"},{"id":"2607.13125","title":"Boogu-Image-0.1: Boosting Open Agentic Multimodal Generation via Understanding under a Minimal Budget","created":"2026-07-14","cited_by_count":6,"area":"agents"},{"id":"2608.16887","title":"An Empirical Study of Training Pixel-Space Text-to-Image Diffusion Models","created":"2026-08-17","cited_by_count":6,"area":"diffusion"},{"id":"2602.19497","title":"MICON-Bench: Benchmarking and Enhancing Multi-Image Context Image Generation in Unified Multimodal Models","created":"2026-02-23","cited_by_count":5,"area":null},{"id":"2603.12893","title":"Finite Difference Flow Optimization for RL Post-Training of Text-to-Image Models","created":"2026-03-13","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":"2604.28185","title":"Visual Generation in the New Era: An Evolution from Atomic Mapping to Agentic World Modeling","created":"2026-04-30","cited_by_count":5,"area":"wm"},{"id":"2608.16721","title":"GenRouter: Unified Workflow Routing for Agentic Image Generation","created":"2026-08-17","cited_by_count":5,"area":"agents"},{"id":"2602.14041","title":"BitDance: Scaling Autoregressive Generative Models with Binary Tokens","created":"2026-02-15","cited_by_count":4,"area":null},{"id":"2602.22570","title":"Guidance Matters: Rethinking the Evaluation Pitfall for Text-to-Image Generation","created":"2026-02-26","cited_by_count":4,"area":"diffusion"},{"id":"2604.24023","title":"ServImage: An Image Generation and Editing Benchmark from Real-world Commercial Imaging Services","created":"2026-04-27","cited_by_count":4,"area":null},{"id":"2606.18249","title":"Unified Multimodal Autoregressive Modeling with Shared Context-Visual Tokenizer is Key to Unification","created":"2026-06-16","cited_by_count":4,"area":null},{"id":"2510.20586","title":"GenColorBench: A Color Evaluation Benchmark for Text-to-Image Generation Models","created":"2025-10-23","cited_by_count":3,"area":null},{"id":"2602.21461","title":"VecGlypher: Unified Vector Glyph Generation with Language Models","created":"2026-02-25","cited_by_count":3,"area":null},{"id":"2603.02138","title":"OmniLottie: Generating Vector Animations via Parameterized Lottie Tokens","created":"2026-03-02","cited_by_count":3,"area":null},{"id":"2511.12207","title":"Mixture of States: Routing Token-Level Dynamics for Multimodal Generation","created":"2025-11-15","cited_by_count":2,"area":"diffusion"},{"id":"2512.02899","title":"Glance: Accelerating Diffusion Models with 1 Sample","created":"2025-12-02","cited_by_count":2,"area":"diffusion"},{"id":"2601.04339","title":"Unified Text-Image Generation with Weakness-Targeted Post-Training","created":"2026-01-07","cited_by_count":2,"area":null},{"id":"2602.11980","title":"Spatial Chain-of-Thought: Bridging Understanding and Generation Models for Spatial Reasoning Generation","created":"2026-02-12","cited_by_count":2,"area":"lr"},{"id":"2603.25823","title":"ViGoR-Bench: How Far Are Visual Generative Models From Zero-Shot Visual Reasoners?","created":"2026-03-26","cited_by_count":2,"area":"lr"},{"id":"2606.12575","title":"High-Fidelity Two-Step Image Generation via Teacher-Aligned End-to-End Distillation","created":"2026-06-10","cited_by_count":2,"area":"diffusion"},{"id":"2606.26984","title":"Unison: Benchmarking Unified Multimodal Models via Synergistic Understanding and Generation","created":"2026-06-25","cited_by_count":2,"area":null},{"id":"2607.01642","title":"Multi-Resolution Flow Matching: Training-Free Diffusion Acceleration via Staged Sampling","created":"2026-07-02","cited_by_count":2,"area":"diffusion"},{"id":"2608.19637","title":"TextRefine: Improving Textual Fidelity, Spatial Placement, and Glyph Rendering for Text Editing in Product Posters","created":"2026-08-20","cited_by_count":2,"area":null},{"id":"2609.02349","title":"GlyphAnchor: Enhancing Visual Text Rendering via Position-Anchored Glyph Priors","created":"2026-09-02","cited_by_count":2,"area":null},{"id":"2601.22571","title":"PerfGuard: A Performance-Aware Agent for Visual Content Generation","created":"2026-01-30","cited_by_count":1,"area":"agents"},{"id":"2602.17047","title":"Amber-Image: Efficient Compression of Large-Scale Diffusion Transformers","created":"2026-02-19","cited_by_count":1,"area":"diffusion"},{"id":"2603.25728","title":"PixelSmile: Toward Fine-Grained Facial Expression Editing","created":"2026-03-26","cited_by_count":1,"area":null},{"id":"2605.19639","title":"Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation","created":"2026-05-19","cited_by_count":1,"area":"lr"},{"id":"2606.20100","title":"WeGenBench: A Multidimensional Diagnostic Benchmark towards Text-to-Image Model Optimization","created":"2026-06-18","cited_by_count":1,"area":null},{"id":"2606.20506","title":"FreeStyle: Free Control of Style-Content Dual-Reference Generation from Community LoRA Mining","created":"2026-06-18","cited_by_count":1,"area":null},{"id":"2608.08676","title":"UniSpace: Unified Visual Representation and Scalable Multimodal Modeling","created":"2026-08-09","cited_by_count":1,"area":null},{"id":"2609.22086","title":"Designer-RSI: Evolving Procedural Memory from User Traffic for Agentic Graphic Design","created":"2026-09-18","cited_by_count":1,"area":"agents"},{"id":"2602.06879","title":"NanoFLUX: Distillation-Driven Compression of Large Text-to-Image Generation Models for Mobile Devices","created":"2026-02-06","cited_by_count":0,"area":"diffusion"},{"id":"2604.22302","title":"Knowledge Visualization: A Benchmark and Method for Knowledge-Intensive Text-to-Image Generation","created":"2026-04-24","cited_by_count":0,"area":null},{"id":"2605.19839","title":"When Preference Labels Fall Short: Aligning Diffusion Models from Real Data","created":"2026-05-19","cited_by_count":0,"area":"diffusion"},{"id":"2606.27089","title":"TMP: Tree-structured Mixed-policy Pruning for Large-scale Image Generation and Editing","created":"2026-06-25","cited_by_count":0,"area":"moe"},{"id":"2607.09133","title":"IB-Flow: Information Bottleneck-Guided CFG Distillation for Few-Step Text-to-Image Generation","created":"2026-07-10","cited_by_count":0,"area":null},{"id":"2608.03357","title":"Can Text-to-Image Models Draw from the Right Frame of Reference?","created":"2026-08-04","cited_by_count":0,"area":null},{"id":"2608.16786","title":"Revisiting Classifier-Free Guidance Methods in Latent Diffusion Models","created":"2026-08-17","cited_by_count":0,"area":"diffusion"},{"id":"2608.24112","title":"Scalable Question-Centric Text-to-Image Evaluation: Reliable Ranking, Fine-Grained Diagnosis, and Cost-Aware Routing","created":"2026-08-25","cited_by_count":0,"area":null},{"id":"2609.35767","title":"Learning Native Reflection in Unified Models with Interleaved Reinforcement Learning","created":"2026-09-28","cited_by_count":0,"area":null},{"id":"2610.01382","title":"Gacha Decoding: Eliciting Diverse Generations Through Instruction Following","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.05453","title":"The Poisoned Conversation: Privacy-Leaking Watermarks in Unified Multimodal Models","created":"2026-10-04","cited_by_count":0,"area":"safety"},{"id":"2610.09450","title":"Iris-3B: Going Beyond the Latent with Pixel-Space Diffusion Training, Conversion and Fine-Tuning","created":"2026-10-07","cited_by_count":0,"area":"diffusion"},{"id":"2610.13944","title":"InstantFusion: A Shared Latent Interface for Heterogeneous Image Generators","created":"2026-10-09","cited_by_count":0,"area":null},{"id":"2610.18097","title":"APT: Feedback-Driven Agentic Post-Training for Text-to-Image Generation","created":"2026-10-13","cited_by_count":0,"area":"agents"},{"id":"2610.19551","title":"TextVerifier: Seeing Beyond Recognition to Verify Chinese Text Rendering","created":"2026-10-14","cited_by_count":0,"area":null}],"next_cursor":null}