{"total":70,"rows":[{"id":"2412.10302","title":"DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding","created":"2024-12-13","cited_by_count":572,"area":"mllm"},{"id":"2501.00321","title":"OCRBench v2: An Improved Benchmark for Evaluating Large Multimodal Models on Visual Text Localization and Reasoning","created":"2024-12-31","cited_by_count":173,"area":"mllm"},{"id":"2505.16933","title":"LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning","created":"2025-05-22","cited_by_count":148,"area":"mllm"},{"id":"2502.09838","title":"HealthGPT: A Medical Large Vision-Language Model for Unifying Comprehension and Generation via Heterogeneous Knowledge Adaptation","created":"2025-02-14","cited_by_count":114,"area":"mllm"},{"id":"2412.06673","title":"ILLUME: Illuminating Your LLMs to See, Draw, and Self-Enhance","created":"2024-12-09","cited_by_count":64,"area":"mllm"},{"id":"2506.13759","title":"Discrete Diffusion in Large Language and Multimodal Models: A Survey","created":"2025-06-16","cited_by_count":61,"area":"mllm"},{"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":"2411.17762","title":"MUSE-VL: Modeling Unified VLM through Semantic Discrete Encoding","created":"2024-11-26","cited_by_count":44,"area":"mllm"},{"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":"2502.06788","title":"EVEv2: Improved Baselines for Encoder-Free Vision-Language Models","created":"2025-02-10","cited_by_count":41,"area":"mllm"},{"id":"2411.16856","title":"SAR3D: Autoregressive 3D Object Generation and Understanding via Multi-scale 3D VQVAE","created":"2024-11-25","cited_by_count":39,"area":"mllm"},{"id":"2507.02664","title":"AIGI-Holmes: Towards Explainable and Generalizable AI-Generated Image Detection via Multimodal Large Language Models","created":"2025-07-03","cited_by_count":33,"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":"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":"2504.14666","title":"Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens","created":"2025-04-20","cited_by_count":28,"area":"mllm"},{"id":"2504.08358","title":"LMM4LMM: Benchmarking and Evaluating Large-multimodal Image Generation with LMMs","created":"2025-04-11","cited_by_count":24,"area":"mllm"},{"id":"2505.23380","title":"UniRL: Self-Improving Unified Multimodal Models via Supervised and Reinforcement Learning","created":"2025-05-29","cited_by_count":24,"area":"mllm"},{"id":"2502.17514","title":"SAE-V: Interpreting Multimodal Models for Enhanced Alignment","created":"2025-02-22","cited_by_count":23,"area":"mllm"},{"id":"2504.20998","title":"YoChameleon: Personalized Vision and Language Generation","created":"2025-04-29","cited_by_count":20,"area":"mllm"},{"id":"2506.23115","title":"MoCa: Modality-aware Continual Pre-training Makes Better Bidirectional Multimodal Embeddings","created":"2025-06-29","cited_by_count":20,"area":"mllm"},{"id":"2502.12148","title":"HermesFlow: Seamlessly Closing the Gap in Multimodal Understanding and Generation","created":"2025-02-17","cited_by_count":18,"area":"mllm"},{"id":"2503.10127","title":"PlanGen: Towards Unified Layout Planning and Image Generation in Auto-Regressive Vision Language Models","created":"2025-03-13","cited_by_count":18,"area":"mllm"},{"id":"2505.24867","title":"Time Blindness: Why Video-Language Models Can't See What Humans Can?","created":"2025-05-30","cited_by_count":18,"area":"mllm"},{"id":"2506.09040","title":"Autoregressive Semantic Visual Reconstruction Helps VLMs Understand Better","created":"2025-06-10","cited_by_count":17,"area":"mllm"},{"id":"2412.01824","title":"X-Prompt: Towards Universal In-Context Image Generation in Auto-Regressive Vision Language Foundation Models","created":"2024-12-02","cited_by_count":15,"area":"mllm"},{"id":"2509.26641","title":"Query-Kontext: An Unified Multimodal Model for Image Generation and Editing","created":"2025-09-30","cited_by_count":15,"area":"mllm"},{"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":"2507.22920","title":"Discrete Tokenization for Multimodal LLMs: A Comprehensive Survey","created":"2025-07-21","cited_by_count":8,"area":"mllm"},{"id":"2511.14760","title":"UniGen-1.5: Enhancing Image Generation and Editing through Reward Unification in Reinforcement Learning","created":"2025-11-18","cited_by_count":8,"area":"mllm"},{"id":"2601.06965","title":"Unified Personalized Understanding, Generating and Editing","created":"2026-01-11","cited_by_count":8,"area":"mllm"},{"id":"2504.06925","title":"Are Vision-Language Models Ready for Dietary Assessment? Exploring the Next Frontier in AI-Powered Food Image Recognition","created":"2025-04-09","cited_by_count":7,"area":"mllm"},{"id":"2506.18504","title":"Generalizing vision-language models to novel domains: A comprehensive survey","created":"2025-06-23","cited_by_count":7,"area":"mllm"},{"id":"2601.21262","title":"CausalEmbed: Auto-Regressive Multi-Vector Generation in Latent Space for Visual Document Embedding","created":"2026-01-29","cited_by_count":7,"area":"mllm"},{"id":"2512.13752","title":"STAR: STacked AutoRegressive Scheme for Unified Multimodal Learning","created":"2025-12-15","cited_by_count":6,"area":"mllm"},{"id":"2505.16149","title":"When VLMs Meet Image Classification: Test Sets Renovation via Missing Label Identification","created":"2025-05-22","cited_by_count":5,"area":"mllm"},{"id":"2509.19018","title":"OmniBridge: Unified Multimodal Understanding, Generation, and Retrieval via Latent Space Alignment","created":"2025-09-23","cited_by_count":5,"area":"mllm"},{"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":"2505.21389","title":"AutoJudger: An Agent-Driven Framework for Efficient Benchmarking of MLLMs","created":"2025-05-27","cited_by_count":4,"area":"mllm"},{"id":"2510.01546","title":"Growing Visual Generative Capacity for Pre-Trained MLLMs","created":"2025-10-02","cited_by_count":4,"area":"mllm"},{"id":"2511.19641","title":"On the Utility of Foundation Models for Fast MRI: Vision-Language-Guided Image Reconstruction","created":"2025-11-24","cited_by_count":4,"area":"mllm"},{"id":"2512.02351","title":"Understanding and Harnessing Sparsity in Unified Multimodal Models","created":"2025-12-02","cited_by_count":4,"area":"mllm"},{"id":"2510.06529","title":"VUGEN: Visual Understanding priors for GENeration","created":"2025-10-08","cited_by_count":3,"area":"mllm"},{"id":"2603.14957","title":"CyCLeGen: Cycle-Consistent Layout Prediction and Image Generation in Vision Foundation Models","created":"2026-03-16","cited_by_count":3,"area":"mllm"},{"id":"2605.16745","title":"EVA01: Unified Native 3D Understanding and Generation via Mixture-of-Transformers","created":"2026-05-16","cited_by_count":3,"area":"mllm"},{"id":"2507.23382","title":"MPCC: A Novel Benchmark for Multimodal Planning with Complex Constraints in Multimodal Large Language Models","created":"2025-07-31","cited_by_count":2,"area":"mllm"},{"id":"2510.11509","title":"Situat3DChange: Situated 3D Change Understanding Dataset for Multimodal Large Language Model","created":"2025-10-13","cited_by_count":2,"area":"mllm"},{"id":"2510.12974","title":"Scope: Selective Cross-modal Orchestration of Visual Perception Experts","created":"2025-10-14","cited_by_count":2,"area":"mllm"},{"id":"2511.23469","title":"Visual Generation Tuning","created":"2025-11-28","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":"2603.24079","title":"When Understanding Becomes a Risk: Authenticity and Safety Risks in the Emerging Image Generation Paradigm","created":"2026-03-25","cited_by_count":2,"area":"mllm"},{"id":"2605.12305","title":"Images in Sentences: Scaling Interleaved Instructions for Unified Visual Generation","created":"2026-05-12","cited_by_count":2,"area":"mllm"},{"id":"2609.16057","title":"OmniHarness: Harnessing Generalizable Visual Generation via Symbolic Policy Learning","created":"2026-09-13","cited_by_count":2,"area":"mllm"},{"id":"2502.07905","title":"DeepSeek on a Trip: Inducing Targeted Visual Hallucinations via Representation Vulnerabilities","created":"2025-02-11","cited_by_count":1,"area":"mllm"},{"id":"2506.02015","title":"OSPO: Object-Centric Self-Improving Preference Optimization for Text-to-Image Generation","created":"2025-05-28","cited_by_count":1,"area":"mllm"},{"id":"2512.02536","title":"WeMMU: Enhanced Bridging of Vision-Language Models and Diffusion Models via Noisy Query Tokens","created":"2025-12-02","cited_by_count":1,"area":"mllm"},{"id":"2512.05422","title":"ParaUni: Enhance Generation in Unified Multimodal Model with Reinforcement-driven Hierarchical Parallel Information Interaction","created":"2025-12-05","cited_by_count":1,"area":"mllm"},{"id":"2602.23711","title":"Can Unified Generation and Understanding Models Maintain Semantic Equivalence Across Different Output Modalities?","created":"2026-02-27","cited_by_count":1,"area":"mllm"},{"id":"2605.15792","title":"Reversing the Flow: Generation-to-Understanding Synergy in Large Multimodal Models","created":"2026-05-15","cited_by_count":1,"area":"mllm"},{"id":"2606.01503","title":"On the Limits of Token Reduction for Efficient Unified Vision Language Training","created":"2026-05-31","cited_by_count":1,"area":"mllm"},{"id":"2606.11188","title":"ARM: An AutoRegressive Large Multimodal Model with Unified Discrete Representations","created":"2026-06-09","cited_by_count":1,"area":"mllm"},{"id":"2608.12209","title":"Generation as Auxiliary Supervision: Enhancing Visual Understanding at Zero Inference Overhead via Decoupled Embedding Prediction","created":"2026-08-12","cited_by_count":1,"area":"mllm"},{"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":"2511.11831","title":"TopoPerception: A Shortcut-Free Evaluation of Global Visual Perception in Large Vision-Language Models","created":"2025-11-14","cited_by_count":0,"area":"mllm"},{"id":"2602.03533","title":"PnP-U3D: Plug-and-Play 3D Framework Bridging Autoregression and Diffusion for Unified Understanding and Generation","created":"2026-02-03","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":"2607.25948","title":"MODUS: Decoder-Only Any-to-Any Modeling of Diverse Modalities","created":"2026-07-28","cited_by_count":0,"area":"mllm"},{"id":"2608.20382","title":"Decoupled Vision-Language System for Multimodal Understanding and Generation","created":"2026-06-29","cited_by_count":0,"area":"mllm"},{"id":"2610.00341","title":"UnifiedAttack: Evaluating the Safety of Large Multimodal Models in Synergistic Harmful Image-Text Generation","created":"2026-09-29","cited_by_count":0,"area":"mllm"},{"id":"2610.13790","title":"OccludeBench: Can VLMs Find What's Missing?","created":"2026-10-09","cited_by_count":0,"area":"mllm"}],"next_cursor":null}