{"total":64,"rows":[{"id":"2505.14683","title":"Emerging Properties in Unified Multimodal Pretraining","created":"2025-05-20","cited_by_count":897,"area":null},{"id":"2506.15564","title":"Show-o2: Improved Native Unified Multimodal Models","created":"2025-06-18","cited_by_count":250,"area":"diffusion"},{"id":"2505.17685","title":"FutureSightDrive: Thinking Visually with Spatio-Temporal CoT for Autonomous Driving","created":"2025-05-23","cited_by_count":166,"area":"vla"},{"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":"2505.02567","title":"Unified Multimodal Understanding and Generation Models: Advances, Challenges, and Opportunities","created":"2025-05-05","cited_by_count":85,"area":null},{"id":"2503.21979","title":"Harmonizing Visual Representations for Unified Multimodal Understanding and Generation","created":"2025-03-27","cited_by_count":74,"area":null},{"id":"2508.05606","title":"Uni-cot: Towards Unified Chain-of-Thought Reasoning Across Text and Vision","created":"2025-08-07","cited_by_count":56,"area":"lr"},{"id":"2505.23606","title":"Muddit: Liberating Generation Beyond Text-to-Image with a Unified Discrete Diffusion Model","created":"2025-05-29","cited_by_count":55,"area":"diffusion"},{"id":"2504.01934","title":"ILLUME+: Illuminating Unified MLLM with Dual Visual Tokenization and Diffusion Refinement","created":"2025-04-02","cited_by_count":54,"area":null},{"id":"2505.05422","title":"TokLIP: Marry Visual Tokens to CLIP for Multimodal Comprehension and Generation","created":"2025-05-08","cited_by_count":51,"area":null},{"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":"2506.18898","title":"Vision as a Dialect: Unifying Visual Understanding and Generation via Text-Aligned Representations","created":"2025-06-23","cited_by_count":44,"area":"mllm"},{"id":"2507.23278","title":"UniLiP: Adapting CLIP for Unified Multimodal Understanding, Generation and Editing","created":"2025-07-31","cited_by_count":44,"area":null},{"id":"2503.14324","title":"DualToken: Towards Unifying Visual Understanding and Generation with Dual Visual Vocabularies","created":"2025-03-18","cited_by_count":42,"area":null},{"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":"2509.25162","title":"AlignTok: Aligning Visual Foundation Encoders to Tokenizers for Diffusion Models","created":"2025-09-29","cited_by_count":36,"area":"diffusion"},{"id":"2503.19839","title":"FireEdit: Fine-grained Instruction-based Image Editing via Region-aware Vision Language Model","created":"2025-03-25","cited_by_count":32,"area":"mllm"},{"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":"2505.24875","title":"ReasonGen-R1: CoT for Autoregressive Image generation models through SFT and RL","created":"2025-05-30","cited_by_count":30,"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":"2503.06764","title":"SemHiTok: A Unified Image Tokenizer via Semantic-Guided Hierarchical Codebook for Multimodal Understanding and Generation","created":"2025-03-09","cited_by_count":21,"area":null},{"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":"2502.13081","title":"Personalized Image Generation with Deep Generative Models: A Decade Survey","created":"2025-02-18","cited_by_count":20,"area":null},{"id":"2508.02317","title":"VeOmni: Scaling Any Modality Model Training with Model-Centric Distributed Recipe Zoo","created":"2025-08-04","cited_by_count":20,"area":"moe"},{"id":"2505.17534","title":"Co-Reinforcement Learning for Unified Multimodal Understanding and Generation","created":"2025-05-23","cited_by_count":15,"area":"lr"},{"id":"2509.18824","title":"Hyper-Bagel: A Unified Acceleration Framework for Multimodal Understanding and Generation","created":"2025-09-23","cited_by_count":13,"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":"2511.20520","title":"HBridge: H-Shape Bridging of Heterogeneous Experts for Unified Multimodal Understanding and Generation","created":"2025-11-25","cited_by_count":11,"area":"diffusion"},{"id":"2508.11952","title":"UniUGG: Unified 3D Understanding and Generation via Geometric-Semantic Encoding","created":"2025-08-16","cited_by_count":10,"area":null},{"id":"2602.21952","title":"MindDriver: Introducing Progressive Multimodal Reasoning for Autonomous Driving","created":"2026-02-25","cited_by_count":10,"area":"lr"},{"id":"2506.07963","title":"SUDER: Self-Improving Unified Large Multimodal Models for Understanding and Generation with Dual Self-Rewards","created":"2025-06-09","cited_by_count":8,"area":"mllm"},{"id":"2507.22920","title":"Discrete Tokenization for Multimodal LLMs: A Comprehensive Survey","created":"2025-07-21","cited_by_count":8,"area":"mllm"},{"id":"2509.21912","title":"Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching","created":"2025-09-26","cited_by_count":6,"area":"diffusion"},{"id":"2512.03125","title":"Mitigating Intra- and Inter-modal Forgetting in Continual Learning of Unified Multimodal Models","created":"2025-12-02","cited_by_count":6,"area":null},{"id":"2512.06750","title":"UARE: A Unified Vision-Language Model for Image Quality Assessment, Restoration, and Enhancement","created":"2025-12-07","cited_by_count":5,"area":"mllm"},{"id":"2603.25706","title":"Wan-Weaver: Interleaved Multi-modal Generation via Decoupled Training","created":"2026-03-26","cited_by_count":5,"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":"2603.09538","title":"Towards Unified Multimodal Interleaved Generation via Group Relative Policy Optimization","created":"2026-03-10","cited_by_count":4,"area":"lr"},{"id":"2605.12495","title":"AlphaGRPO: Unlocking Self-Reflective Multimodal Generation in UMMs via Decompositional Verifiable Reward","created":"2026-05-12","cited_by_count":4,"area":"lr"},{"id":"2605.31604","title":"Representation Forcing for Bottleneck-Free Unified Multimodal Models","created":"2026-05-29","cited_by_count":4,"area":null},{"id":"2602.06442","title":"ChatUMM: Robust Context Tracking for Conversational Interleaved Generation","created":"2026-02-06","cited_by_count":3,"area":null},{"id":"2603.09471","title":"OmniEarth: A Benchmark for Evaluating Vision-Language Models in Geospatial Tasks","created":"2026-03-10","cited_by_count":3,"area":"lr"},{"id":"2606.17296","title":"Pareto LoRA: Mitigating Modality Imbalance in Unified Multimodal Models via Pareto-Optimal Gradient Integration","created":"2026-06-15","cited_by_count":3,"area":null},{"id":"2609.08282","title":"Dreaming in Flow: Generative Grounding Feedback for Self-Evolving Unified Multimodal Models","created":"2026-09-08","cited_by_count":3,"area":null},{"id":"2506.03591","title":"Resolving Task Objective Conflicts in Unified Model via Task-Aware Mixture-of-Experts","created":"2025-06-04","cited_by_count":2,"area":"mllm"},{"id":"2603.12108","title":"EvoTok: A Unified Image Tokenizer via Residual Latent Evolution for Visual Understanding and Generation","created":"2026-03-12","cited_by_count":2,"area":"mllm"},{"id":"2603.20209","title":"Children's Intelligence Tests Pose Challenges for MLLMs? KidGym: A 2D Grid-Based Reasoning Benchmark for MLLMs","created":"2026-03-02","cited_by_count":2,"area":"lr"},{"id":"2605.08029","title":"STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation","created":"2026-05-08","cited_by_count":2,"area":"inference"},{"id":"2605.27374","title":"ICG: Improving Cover Image Generation via MLLM-based Prompting and Personalized Preference Alignment","created":"2026-04-08","cited_by_count":2,"area":"mllm"},{"id":"2509.14738","title":"UnifiedVisual: A Framework for Constructing Unified Vision-Language Datasets","created":"2025-09-18","cited_by_count":1,"area":null},{"id":"2510.25682","title":"PairUni: Pairwise Training for Unified Multimodal Language Models","created":"2025-10-29","cited_by_count":1,"area":"mllm"},{"id":"2603.27693","title":"LVRPO: Language-Visual Alignment with GRPO for Multimodal Understanding and Generation","created":"2026-03-29","cited_by_count":1,"area":"lr"},{"id":"2604.16552","title":"Co-generation of Layout and Shape from Text via Autoregressive 3D Diffusion","created":"2026-04-17","cited_by_count":1,"area":null},{"id":"2604.25636","title":"Refinement via Regeneration: Enlarging Modification Space Boosts Image Refinement in Unified Multimodal Models","created":"2026-04-28","cited_by_count":1,"area":null},{"id":"2605.18115","title":"WinTok: A Win-Win Hybrid Tokenizer via Decomposing Visual Understanding and Generation with Transferable Tokens","created":"2026-05-18","cited_by_count":1,"area":null},{"id":"2609.38597","title":"PixelUMM: Encoder-Free Unified Image and Video Understanding and Generation","created":"2026-09-29","cited_by_count":1,"area":"mllm"},{"id":"2506.20214","title":"UniCode$^2$: Cascaded Large-scale Codebooks for Unified Multimodal Understanding and Generation","created":"2025-06-25","cited_by_count":0,"area":"mllm"},{"id":"2602.14178","title":"UniWeTok: An Unified Binary Tokenizer with Codebook Size $\\mathit{2^{128}}$ for Unified Multimodal Large Language Model","created":"2026-02-15","cited_by_count":0,"area":"mllm"},{"id":"2606.04457","title":"Imagine Before You Draw: Visual Prompt Engineering for Image Generation","created":"2026-06-03","cited_by_count":0,"area":null},{"id":"2607.11886","title":"Read It Back: Pretrained MLLMs Are Zero-Shot Reward Models for Text-to-Image Generation","created":"2026-07-13","cited_by_count":0,"area":"alignment"},{"id":"2608.28603","title":"C3-UniMM: Causal Cycle-Consistent Unified Multimodal Modeling via Super Alignment and Shared Decoding Space","created":"2026-07-04","cited_by_count":0,"area":null},{"id":"2609.07815","title":"VoT: Vision-of-Thought for Unified Multimodal Representation Alignment","created":"2026-09-07","cited_by_count":0,"area":"lr"},{"id":"2609.35767","title":"Learning Native Reflection in Unified Models with Interleaved Reinforcement Learning","created":"2026-09-28","cited_by_count":0,"area":null}],"next_cursor":null}