{"total":129,"rows":[{"id":"2206.02779","title":"Blended Latent Diffusion","created":"2022-06-06","cited_by_count":432,"area":"mllm"},{"id":"2309.11499","title":"DreamLLM: Synergistic Multimodal Comprehension and Creation","created":"2023-09-20","cited_by_count":297,"area":"mllm"},{"id":"2402.12226","title":"AnyGPT: Unified Multimodal LLM with Discrete Sequence Modeling","created":"2024-02-19","cited_by_count":217,"area":"mllm"},{"id":"2104.03135","title":"Seeing Out of tHe bOx: End-to-End Pre-training for Vision-Language Representation Learning","created":"2021-04-07","cited_by_count":187,"area":"mllm"},{"id":"2309.02591","title":"Scaling Autoregressive Multi-Modal Models: Pretraining and Instruction Tuning","created":"2023-09-05","cited_by_count":170,"area":"mllm"},{"id":"2405.20797","title":"Ovis: Structural Embedding Alignment for Multimodal Large Language Model","created":"2024-05-31","cited_by_count":169,"area":"mllm"},{"id":"2402.05755","title":"Spirit LM: Interleaved Spoken and Written Language Model","created":"2024-02-08","cited_by_count":126,"area":"mllm"},{"id":"2407.06135","title":"ANOLE: An Open, Autoregressive, Native Large Multimodal Models for Interleaved Image-Text Generation","created":"2024-07-08","cited_by_count":114,"area":"mllm"},{"id":"2402.03161","title":"Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization","created":"2024-02-05","cited_by_count":100,"area":"mllm"},{"id":"2305.05726","title":"Vision-Language Models in Remote Sensing: Current Progress and Future Trends","created":"2023-05-09","cited_by_count":93,"area":"mllm"},{"id":"2510.07077","title":"Vision-Language-Action Models for Robotics: A Review Towards Real-World Applications","created":"2025-10-08","cited_by_count":84,"area":"mllm"},{"id":"2308.03685","title":"Learning Concise and Descriptive Attributes for Visual Recognition","created":"2023-08-07","cited_by_count":73,"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":"2410.09575","title":"Reconstructive Visual Instruction Tuning","created":"2024-10-12","cited_by_count":55,"area":"mllm"},{"id":"2412.08635","title":"Multimodal Latent Language Modeling with Next-Token Diffusion","created":"2024-12-11","cited_by_count":48,"area":"mllm"},{"id":"2411.19722","title":"JetFormer: An Autoregressive Generative Model of Raw Images and Text","created":"2024-11-29","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":"2311.17618","title":"ShapeGPT: 3D Shape Generation with A Unified Multi-modal Language Model","created":"2023-11-29","cited_by_count":39,"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":"2506.01853","title":"ShapeLLM-Omni: A Native Multimodal LLM for 3D Generation and Understanding","created":"2025-06-02","cited_by_count":38,"area":"mllm"},{"id":"2601.05640","title":"SGDrive: Scene-to-Goal Hierarchical World Cognition for Autonomous Driving","created":"2026-01-09","cited_by_count":38,"area":"mllm"},{"id":"2303.14865","title":"Revisiting Multimodal Representation in Contrastive Learning: From Patch and Token Embeddings to Finite Discrete Tokens","created":"2023-03-27","cited_by_count":35,"area":"mllm"},{"id":"2406.07904","title":"Grounding Multimodal Large Language Models in Actions","created":"2024-06-12","cited_by_count":35,"area":"mllm"},{"id":"2309.03179","title":"SLiMe: Segment Like Me","created":"2023-09-06","cited_by_count":34,"area":"mllm"},{"id":"2406.14294","title":"DASB - Discrete Audio and Speech Benchmark","created":"2024-06-20","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":"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":"2402.10805","title":"Generative Cross-Modal Retrieval: Memorizing Images in Multimodal Language Models for Retrieval and Beyond","created":"2024-02-16","cited_by_count":28,"area":"mllm"},{"id":"2409.18127","title":"EgoLM: Multi-Modal Language Model of Egocentric Motions","created":"2024-09-26","cited_by_count":28,"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":"2507.19024","title":"A Survey of Multimodal Hallucination Evaluation and Detection","created":"2025-07-25","cited_by_count":27,"area":"mllm"},{"id":"2305.20087","title":"Too Large; Data Reduction for Vision-Language Pre-Training","created":"2023-05-31","cited_by_count":26,"area":"mllm"},{"id":"2402.11248","title":"CoLLaVO: Crayon Large Language and Vision mOdel","created":"2024-02-17","cited_by_count":26,"area":"mllm"},{"id":"2310.06311","title":"Improving Compositional Text-to-image Generation with Large Vision-Language Models","created":"2023-10-10","cited_by_count":24,"area":"mllm"},{"id":"2503.13026","title":"HiMTok: Learning Hierarchical Mask Tokens for Image Segmentation with Large Multimodal Model","created":"2025-03-17","cited_by_count":20,"area":"mllm"},{"id":"2509.11986","title":"Lost in Embeddings: Information Loss in Vision-Language Models","created":"2025-09-15","cited_by_count":20,"area":"mllm"},{"id":"2510.20639","title":"Better Tokens for Better 3D: Advancing Vision-Language Modeling in 3D Medical Imaging","created":"2025-10-23","cited_by_count":20,"area":"mllm"},{"id":"2512.08240","title":"Hybrid Token Compression for Vision-Language Models","created":"2025-12-09","cited_by_count":20,"area":"mllm"},{"id":"2203.09067","title":"UNIMO-2: End-to-End Unified Vision-Language Grounded Learning","created":"2022-03-17","cited_by_count":19,"area":"mllm"},{"id":"2503.12926","title":"Task-Oriented Feature Compression for Multimodal Understanding via Device-Edge Co-Inference","created":"2025-03-17","cited_by_count":18,"area":"mllm"},{"id":"2602.15397","title":"ActionCodec: What Makes for Good Action Tokenizers","created":"2026-02-17","cited_by_count":18,"area":"mllm"},{"id":"2206.07699","title":"Write and Paint: Generative Vision-Language Models are Unified Modal Learners","created":"2022-06-15","cited_by_count":17,"area":"mllm"},{"id":"2505.16326","title":"ChemMLLM: Chemical Multimodal Large Language Model","created":"2025-05-22","cited_by_count":17,"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":"2203.14395","title":"Single-Stream Multi-Level Alignment for Vision-Language Pretraining","created":"2022-03-27","cited_by_count":16,"area":"mllm"},{"id":"2410.02155","title":"From Pixels to Tokens: Byte-Pair Encoding on Quantized Visual Modalities","created":"2024-10-03","cited_by_count":16,"area":"mllm"},{"id":"2505.23043","title":"Cross-Task Generalization Between Understanding and Generation in Unified Vision-Language Models: A Controlled Study","created":"2025-05-29","cited_by_count":15,"area":"mllm"},{"id":"2509.16197","title":"MANZANO: A Simple and Scalable Unified Multimodal Model with a Hybrid Vision Tokenizer","created":"2025-09-19","cited_by_count":15,"area":"mllm"},{"id":"2511.02776","title":"XR-1: Towards Versatile Vision-Language-Action Models via Learning Unified Vision-Motion Representations","created":"2025-11-04","cited_by_count":15,"area":"mllm"},{"id":"2403.09072","title":"UniCode: Learning a Unified Codebook for Multimodal Large Language Models","created":"2024-03-14","cited_by_count":14,"area":"mllm"},{"id":"2508.03742","title":"Boosting Vision Semantic Density with Anatomy Normality Modeling for Medical Vision-language Pre-training","created":"2025-08-01","cited_by_count":14,"area":"mllm"},{"id":"2402.01293","title":"Can MLLMs Perform Text-to-Image In-Context Learning?","created":"2024-02-02","cited_by_count":13,"area":"mllm"},{"id":"2405.08815","title":"Efficient Vision-Language Pre-training by Cluster Masking","created":"2024-05-14","cited_by_count":13,"area":"mllm"},{"id":"2406.05814","title":"TIGeR: Unifying Text-to-Image Generation and Retrieval with Large Multimodal Models","created":"2024-06-09","cited_by_count":12,"area":"mllm"},{"id":"2602.18532","title":"VLANeXt: Recipes for Building Strong VLA Models","created":"2026-02-20","cited_by_count":12,"area":"mllm"},{"id":"2208.09374","title":"VLMAE: Vision-Language Masked Autoencoder","created":"2022-08-19","cited_by_count":11,"area":"mllm"},{"id":"2312.07408","title":"Turbo: Informativity-Driven Acceleration Plug-In for Vision-Language Models","created":"2023-12-12","cited_by_count":11,"area":"mllm"},{"id":"2412.00142","title":"Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features","created":"2024-11-28","cited_by_count":11,"area":"mllm"},{"id":"2503.01019","title":"MedUnifier: Unifying Vision-and-Language Pre-training on Medical Data with Vision Generation Task using Discrete Visual Representations","created":"2025-03-02","cited_by_count":11,"area":"mllm"},{"id":"2503.14694","title":"HaploVL: A Single-Transformer Baseline for Multi-Modal Understanding","created":"2025-03-12","cited_by_count":11,"area":"mllm"},{"id":"2512.12768","title":"CoRe3D: Collaborative Reasoning as a Foundation for 3D Intelligence","created":"2025-12-14","cited_by_count":10,"area":"mllm"},{"id":"2311.01441","title":"Distilling Out-of-Distribution Robustness from Vision-Language Foundation Models","created":"2023-11-02","cited_by_count":9,"area":"mllm"},{"id":"2411.17773","title":"Efficient Multi-modal Large Language Models via Visual Token Grouping","created":"2024-11-26","cited_by_count":9,"area":"mllm"},{"id":"2505.05098","title":"X-Driver: Explainable Autonomous Driving with Vision-Language Models","created":"2025-05-08","cited_by_count":9,"area":"mllm"},{"id":"2506.23639","title":"Unified Multimodal Understanding via Byte-Pair Visual Encoding","created":"2025-06-30","cited_by_count":9,"area":"mllm"},{"id":"2409.14993","title":"Multi-modal Generative AI: Multi-modal LLMs, Diffusions, and the Unification","created":"2024-09-23","cited_by_count":8,"area":"mllm"},{"id":"2504.14245","title":"Towards Explainable Fake Image Detection with Multi-Modal Large Language Models","created":"2025-04-19","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":"2311.04589","title":"TEAL: Tokenize and Embed ALL for Multi-modal Large Language Models","created":"2023-11-08","cited_by_count":7,"area":"mllm"},{"id":"2405.15728","title":"Disease-informed Adaptation of Vision-Language Models","created":"2024-05-24","cited_by_count":7,"area":"mllm"},{"id":"2503.12446","title":"BREEN: Bridge Data-Efficient Encoder-Free Multimodal Learning with Learnable Queries","created":"2025-03-16","cited_by_count":7,"area":"mllm"},{"id":"2505.17726","title":"Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM","created":"2025-05-23","cited_by_count":7,"area":"mllm"},{"id":"2502.03429","title":"On Fairness of Unified Multimodal Large Language Model for Image Generation","created":"2025-02-05","cited_by_count":6,"area":"mllm"},{"id":"2505.16495","title":"ALTo: Adaptive-Length Tokenizer for Autoregressive Mask Generation","created":"2025-05-22","cited_by_count":6,"area":"mllm"},{"id":"2505.21547","title":"Image Tokens Matter: Mitigating Hallucination in Discrete Tokenizer-based Large Vision-Language Models via Latent Editing","created":"2025-05-24","cited_by_count":5,"area":"mllm"},{"id":"2309.08531","title":"Towards Practical and Efficient Image-to-Speech Captioning with Vision-Language Pre-training and Multi-modal Tokens","created":"2023-09-15","cited_by_count":4,"area":"mllm"},{"id":"2503.19647","title":"Show or Tell? Effectively prompting Vision-Language Models for semantic segmentation","created":"2025-03-25","cited_by_count":4,"area":"mllm"},{"id":"2507.07104","title":"Vision-Language-Vision Auto-Encoder: Scalable Knowledge Distillation from Diffusion Models","created":"2025-07-09","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":"2510.02987","title":"TIT-Score: Evaluating Long-Prompt Based Text-to-Image Alignment via Text-to-Image-to-Text Consistency","created":"2025-10-03","cited_by_count":4,"area":"mllm"},{"id":"2312.11171","title":"UniDCP: Unifying Multiple Medical Vision-language Tasks via Dynamic Cross-modal Learnable Prompts","created":"2023-12-18","cited_by_count":3,"area":"mllm"},{"id":"2507.06140","title":"LangMamba: A Language-driven Mamba Framework for Low-dose CT Denoising with Vision-language Models","created":"2025-07-08","cited_by_count":3,"area":"mllm"},{"id":"2508.09857","title":"OneVAE: Joint Discrete and Continuous Optimization Helps Discrete Video VAE Train Better","created":"2025-08-13","cited_by_count":3,"area":"mllm"},{"id":"2510.06529","title":"VUGEN: Visual Understanding priors for GENeration","created":"2025-10-08","cited_by_count":3,"area":"mllm"},{"id":"2601.22714","title":"Vision-Language Models Unlock Task-Centric Latent Actions","created":"2026-01-30","cited_by_count":3,"area":"mllm"},{"id":"2602.11656","title":"SToRM: Supervised Token Reduction for Multi-modal LLMs toward efficient end-to-end autonomous driving","created":"2026-02-12","cited_by_count":3,"area":"mllm"},{"id":"2602.17869","title":"Learning Compact Video Representations for Efficient Long-form Video Understanding in Large Multimodal Models","created":"2026-02-19","cited_by_count":3,"area":"mllm"},{"id":"2603.00732","title":"UniHM: Unified Dexterous Hand Manipulation with Vision Language Model","created":"2026-02-28","cited_by_count":3,"area":"mllm"},{"id":"2603.18795","title":"Perceptio: Perception Enhanced Vision Language Models via Spatial Token Generation","created":"2026-03-19","cited_by_count":3,"area":"mllm"},{"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"},{"id":"2409.09276","title":"Visuo-Tactile Zero-Shot Object Recognition with Vision-Language Model","created":"2024-09-14","cited_by_count":2,"area":"mllm"},{"id":"2410.20109","title":"GiVE: Guiding Visual Encoder to Perceive Overlooked Information","created":"2024-10-26","cited_by_count":2,"area":"mllm"},{"id":"2503.18407","title":"VTD-CLIP: Video-to-Text Discretization via Prompting CLIP","created":"2025-03-24","cited_by_count":2,"area":"mllm"},{"id":"2508.06895","title":"BASIC: Boosting Visual Alignment with Intrinsic Refined Embeddings in Multimodal Large Language Models","created":"2025-08-09","cited_by_count":2,"area":"mllm"},{"id":"2511.23469","title":"Visual Generation Tuning","created":"2025-11-28","cited_by_count":2,"area":"mllm"},{"id":"2601.14968","title":"InstructTime++: Time Series Classification with Multimodal Language Modeling via Implicit Feature Enhancement","created":"2026-01-21","cited_by_count":2,"area":"mllm"},{"id":"2603.09173","title":"Point Cloud as a Foreign Language for Multi-modal Large Language Model","created":"2026-03-10","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"}],"next_cursor":"100"}