{"total":133,"rows":[{"id":"2408.03326","title":"LLaVA-OneVision: Easy Visual Task Transfer","created":"2024-08-06","cited_by_count":2719,"area":"mllm"},{"id":"2408.01800","title":"MiniCPM-V: A GPT-4V Level MLLM on Your Phone","created":"2024-08-03","cited_by_count":1079,"area":"mllm"},{"id":"2404.16821","title":"How Far Are We to GPT-4V? Closing the Gap to Commercial Multimodal Models with Open-Source Suites","created":"2024-04-25","cited_by_count":1050,"area":"mllm"},{"id":"2406.16860","title":"Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMs","created":"2024-06-24","cited_by_count":838,"area":"mllm"},{"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":"2403.18814","title":"Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models","created":"2024-03-27","cited_by_count":365,"area":"mllm"},{"id":"2409.17146","title":"Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models","created":"2024-09-25","cited_by_count":329,"area":"mllm"},{"id":"2408.04840","title":"mPLUG-Owl3: Towards Long Image-Sequence Understanding in Multi-Modal Large Language Models","created":"2024-08-09","cited_by_count":291,"area":"mllm"},{"id":"2501.00574","title":"VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling","created":"2024-12-31","cited_by_count":220,"area":"mllm"},{"id":"2501.12386","title":"InternVideo2.5: Empowering Video MLLMs with Long and Rich Context Modeling","created":"2025-01-21","cited_by_count":211,"area":"mllm"},{"id":"2412.04468","title":"NVILA: Efficient Frontier Visual Language Models","created":"2024-12-05","cited_by_count":209,"area":"mllm"},{"id":"2406.19280","title":"HuatuoGPT-Vision, Towards Injecting Medical Visual Knowledge into Multimodal LLMs at Scale","created":"2024-06-27","cited_by_count":200,"area":"mllm"},{"id":"2407.03320","title":"InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output","created":"2024-07-03","cited_by_count":195,"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":"2404.01258","title":"Direct Preference Optimization of Video Large Multimodal Models from Language Model Reward","created":"2024-04-01","cited_by_count":147,"area":"mllm"},{"id":"2406.08394","title":"VisionLLM v2: An End-to-End Generalist Multimodal Large Language Model for Hundreds of Vision-Language Tasks","created":"2024-06-12","cited_by_count":137,"area":"mllm"},{"id":"2502.21257","title":"RoboBrain: A Unified Brain Model for Robotic Manipulation from Abstract to Concrete","created":"2025-02-28","cited_by_count":135,"area":"mllm"},{"id":"2403.20271","title":"Draw-and-Understand: Leveraging Visual Prompts to Enable MLLMs to Comprehend What You Want","created":"2024-03-29","cited_by_count":101,"area":"mllm"},{"id":"2405.10739","title":"Efficient Multimodal Large Language Models: A Survey","created":"2024-05-17","cited_by_count":96,"area":"mllm"},{"id":"2404.18532","title":"MileBench: Benchmarking MLLMs in Long Context","created":"2024-04-29","cited_by_count":88,"area":"mllm"},{"id":"2404.13046","title":"MoVA: Adapting Mixture of Vision Experts to Multimodal Context","created":"2024-04-19","cited_by_count":83,"area":"mllm"},{"id":"2410.08202","title":"Mono-InternVL: Pushing the Boundaries of Monolithic Multimodal Large Language Models with Endogenous Visual Pre-training","created":"2024-10-10","cited_by_count":82,"area":"mllm"},{"id":"2407.08303","title":"DenseFusion-1M: Merging Vision Experts for Comprehensive Multimodal Perception","created":"2024-07-11","cited_by_count":73,"area":"mllm"},{"id":"2501.14818","title":"Eagle 2: Building Post-Training Data Strategies from Scratch for Frontier Vision-Language Models","created":"2025-01-20","cited_by_count":70,"area":"mllm"},{"id":"2410.16153","title":"Pangea: A Fully Open Multilingual Multimodal LLM for 39 Languages","created":"2024-10-21","cited_by_count":64,"area":"mllm"},{"id":"2404.12803","title":"TextSquare: Scaling up Text-Centric Visual Instruction Tuning","created":"2024-04-19","cited_by_count":62,"area":"mllm"},{"id":"2408.01319","title":"A Comprehensive Review of Multimodal Large Language Models: Performance and Challenges Across Different Tasks","created":"2024-08-02","cited_by_count":57,"area":"mllm"},{"id":"2405.05949","title":"CuMo: Scaling Multimodal LLM with Co-Upcycled Mixture-of-Experts","created":"2024-05-09","cited_by_count":56,"area":"mllm"},{"id":"2410.09575","title":"Reconstructive Visual Instruction Tuning","created":"2024-10-12","cited_by_count":55,"area":"mllm"},{"id":"2406.10328","title":"From Pixels to Prose: A Large Dataset of Dense Image Captions","created":"2024-06-14","cited_by_count":54,"area":"mllm"},{"id":"2510.17269","title":"FineVision: Open Data Is All You Need","created":"2025-10-20","cited_by_count":53,"area":"mllm"},{"id":"2406.05127","title":"Towards Semantic Equivalence of Tokenization in Multimodal LLM","created":"2024-06-07","cited_by_count":45,"area":"mllm"},{"id":"2408.15881","title":"LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation","created":"2024-08-28","cited_by_count":45,"area":"mllm"},{"id":"2405.16919","title":"VoCoT: Unleashing Visually Grounded Multi-Step Reasoning in Large Multi-Modal Models","created":"2024-05-27","cited_by_count":43,"area":"mllm"},{"id":"2409.05840","title":"MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct","created":"2024-09-09","cited_by_count":42,"area":"mllm"},{"id":"2504.07957","title":"MM-IFEngine: Towards Multimodal Instruction Following","created":"2025-04-10","cited_by_count":42,"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":"2502.05177","title":"Long-VITA: Scaling Large Multi-modal Models to 1 Million Tokens with Leading Short-Context Accuracy","created":"2025-02-07","cited_by_count":39,"area":"mllm"},{"id":"2407.06438","title":"SOLO: A Single Transformer for Scalable Vision-Language Modeling","created":"2024-07-08","cited_by_count":37,"area":"mllm"},{"id":"2408.11878","title":"Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications","created":"2024-08-20","cited_by_count":36,"area":"mllm"},{"id":"2503.11579","title":"Vamba: Understanding Hour-Long Videos with Hybrid Mamba-Transformers","created":"2025-03-14","cited_by_count":36,"area":"mllm"},{"id":"2406.14544","title":"Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs","created":"2024-06-20","cited_by_count":32,"area":"mllm"},{"id":"2412.09530","title":"Dynamic-VLM: Simple Dynamic Visual Token Compression for VideoLLM","created":"2024-12-12","cited_by_count":32,"area":"mllm"},{"id":"2406.10638","title":"Unveiling the Ignorance of MLLMs: Seeing Clearly, Answering Incorrectly","created":"2024-06-15","cited_by_count":30,"area":"mllm"},{"id":"2411.18363","title":"ChatRex: Taming Multimodal LLM for Joint Perception and Understanding","created":"2024-11-27","cited_by_count":30,"area":"mllm"},{"id":"2412.07689","title":"RoboTron-Drive: All-in-One Large Multimodal Model for Autonomous Driving","created":"2024-12-10","cited_by_count":30,"area":"mllm"},{"id":"2502.07855","title":"Vision-Language Models for Edge Networks: A Comprehensive Survey","created":"2025-02-11","cited_by_count":29,"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":"2605.27365","title":"LocateAnything: Fast and High-Quality Vision-Language Grounding with Parallel Box Decoding","created":"2026-05-26","cited_by_count":28,"area":"mllm"},{"id":"2405.15738","title":"ConvLLaVA: Hierarchical Backbones as Visual Encoder for Large Multimodal Models","created":"2024-05-24","cited_by_count":26,"area":"mllm"},{"id":"2412.05819","title":"[CLS] Token Tells Everything Needed for Training-free Efficient MLLMs","created":"2024-12-08","cited_by_count":26,"area":"mllm"},{"id":"2407.17453","title":"VILA$^2$: VILA Augmented VILA","created":"2024-07-24","cited_by_count":25,"area":"mllm"},{"id":"2411.01106","title":"SV-RAG: LoRA-Contextualizing Adaptation of MLLMs for Long Document Understanding","created":"2024-11-02","cited_by_count":25,"area":"mllm"},{"id":"2411.10640","title":"BlueLM-V-3B: Algorithm and System Co-Design for Multimodal Large Language Models on Mobile Devices","created":"2024-11-16","cited_by_count":25,"area":"mllm"},{"id":"2412.09613","title":"PVC: Progressive Visual Token Compression for Unified Image and Video Processing in Large Vision-Language Models","created":"2024-12-12","cited_by_count":25,"area":"mllm"},{"id":"2410.07177","title":"MM-Ego: Towards Building Egocentric Multimodal LLMs for Video QA","created":"2024-10-09","cited_by_count":24,"area":"mllm"},{"id":"2411.14522","title":"GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AI","created":"2024-11-21","cited_by_count":24,"area":"mllm"},{"id":"2406.03496","title":"Wings: Learning Multimodal LLMs without Text-only Forgetting","created":"2024-06-05","cited_by_count":23,"area":"mllm"},{"id":"2410.06169","title":"Treat Visual Tokens as Text? But Your MLLM Only Needs Fewer Efforts to See","created":"2024-10-08","cited_by_count":23,"area":"mllm"},{"id":"2506.05453","title":"MLLM-CL: Continual Learning for Multimodal Large Language Models","created":"2025-06-05","cited_by_count":23,"area":"mllm"},{"id":"2406.17770","title":"MG-LLaVA: Towards Multi-Granularity Visual Instruction Tuning","created":"2024-06-25","cited_by_count":22,"area":"mllm"},{"id":"2411.14228","title":"FocusLLaVA: A Coarse-to-Fine Approach for Efficient and Effective Visual Token Compression","created":"2024-11-21","cited_by_count":22,"area":"mllm"},{"id":"2501.05901","title":"Valley2: Exploring Multimodal Models with Scalable Vision-Language Design","created":"2025-01-10","cited_by_count":21,"area":"mllm"},{"id":"2405.12107","title":"Imp: Highly Capable Large Multimodal Models for Mobile Devices","created":"2024-05-20","cited_by_count":20,"area":"mllm"},{"id":"2405.17871","title":"Seeing the Image: Prioritizing Visual Correlation by Contrastive Alignment","created":"2024-05-28","cited_by_count":20,"area":"mllm"},{"id":"2410.07167","title":"Deciphering Cross-Modal Alignment in Large Vision-Language Models with Modality Integration Rate","created":"2024-10-09","cited_by_count":20,"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":"2411.02708","title":"Exploring Response Uncertainty in MLLMs: An Empirical Evaluation under Misleading Scenarios","created":"2024-11-05","cited_by_count":19,"area":"mllm"},{"id":"2510.14979","title":"From Pixels to Words -- Towards Native Vision-Language Primitives at Scale","created":"2025-10-16","cited_by_count":18,"area":"mllm"},{"id":"2409.04828","title":"POINTS: Improving Your Vision-language Model with Affordable Strategies","created":"2024-09-07","cited_by_count":17,"area":"mllm"},{"id":"2407.08706","title":"HiRes-LLaVA: Restoring Fragmentation Input in High-Resolution Large Vision-Language Models","created":"2024-07-11","cited_by_count":16,"area":"mllm"},{"id":"2407.18129","title":"Dallah: A Dialect-Aware Multimodal Large Language Model for Arabic","created":"2024-07-25","cited_by_count":16,"area":"mllm"},{"id":"2506.24102","title":"DenseWorld-1M: Towards Detailed Dense Grounded Caption in the Real World","created":"2025-06-30","cited_by_count":16,"area":"mllm"},{"id":"2407.08583","title":"The Synergy between Data and Multi-Modal Large Language Models: A Survey from Co-Development Perspective","created":"2024-07-11","cited_by_count":15,"area":"mllm"},{"id":"2503.08741","title":"Oasis: One Image is All You Need for Multimodal Instruction Data Synthesis","created":"2025-03-11","cited_by_count":14,"area":"mllm"},{"id":"2410.20717","title":"Face-MLLM: A Large Face Perception Model","created":"2024-10-28","cited_by_count":13,"area":"mllm"},{"id":"2507.12566","title":"Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models","created":"2025-07-16","cited_by_count":13,"area":"mllm"},{"id":"2407.19185","title":"LLaVA-Read: Enhancing Reading Ability of Multimodal Language Models","created":"2024-07-27","cited_by_count":12,"area":"mllm"},{"id":"2409.13540","title":"FullAnno: A Data Engine for Enhancing Image Comprehension of MLLMs","created":"2024-09-20","cited_by_count":12,"area":"mllm"},{"id":"2503.21817","title":"Skip-Vision: Efficient and Scalable Acceleration of Vision-Language Models via Adaptive Token Skipping","created":"2025-03-26","cited_by_count":12,"area":"mllm"},{"id":"2407.04923","title":"OmChat: A Recipe to Train Multimodal Language Models with Strong Long Context and Video Understanding","created":"2024-07-06","cited_by_count":11,"area":"mllm"},{"id":"2501.04322","title":"Eve: Efficient Multimodal Vision Language Models with Elastic Visual Experts","created":"2025-01-08","cited_by_count":11,"area":"mllm"},{"id":"2505.17020","title":"CrossLMM: Decoupling Long Video Sequences from LMMs via Dual Cross-Attention Mechanisms","created":"2025-05-22","cited_by_count":11,"area":"mllm"},{"id":"2412.01822","title":"VLsI: Verbalized Layers-to-Interactions from Large to Small Vision Language Models","created":"2024-12-02","cited_by_count":10,"area":"mllm"},{"id":"2412.16158","title":"HoVLE: Unleashing the Power of Monolithic Vision-Language Models with Holistic Vision-Language Embedding","created":"2024-12-20","cited_by_count":10,"area":"mllm"},{"id":"2507.18300","title":"LMM-Det: Make Large Multimodal Models Excel in Object Detection","created":"2025-07-24","cited_by_count":10,"area":"mllm"},{"id":"2410.02745","title":"AVG-LLaVA: An Efficient Large Multimodal Model with Adaptive Visual Granularity","created":"2024-09-20","cited_by_count":9,"area":"mllm"},{"id":"2412.09585","title":"Elevating Visual Perception in Multimodal LLMs with Visual Embedding Distillation","created":"2024-12-12","cited_by_count":9,"area":"mllm"},{"id":"2504.10000","title":"Do We Really Need Curated Malicious Data for Safety Alignment in Multi-modal Large Language Models?","created":"2025-04-14","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":"2406.00977","title":"Dragonfly: Multi-Resolution Zoom-In Encoding Enhances Vision-Language Models","created":"2024-06-03","cited_by_count":8,"area":"mllm"},{"id":"2412.03565","title":"INST-IT: Boosting Instance Understanding via Explicit Visual Prompt Instruction Tuning","created":"2024-12-04","cited_by_count":8,"area":"mllm"},{"id":"2412.11475","title":"OmniVLM: A Token-Compressed, Sub-Billion-Parameter Vision-Language Model for Efficient On-Device Inference","created":"2024-12-16","cited_by_count":8,"area":"mllm"},{"id":"2503.12821","title":"From Head to Tail: Towards Balanced Representation in Large Vision-Language Models through Adaptive Data Calibration","created":"2025-03-17","cited_by_count":8,"area":"mllm"},{"id":"2606.09393","title":"CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning","created":"2026-06-08","cited_by_count":8,"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":"2407.05758","title":"Potential of Multimodal Large Language Models for Data Mining of Medical Images and Free-text Reports","created":"2024-07-08","cited_by_count":6,"area":"mllm"},{"id":"2407.11522","title":"FIRE: A Dataset for Feedback Integration and Refinement Evaluation of Multimodal Models","created":"2024-07-16","cited_by_count":6,"area":"mllm"},{"id":"2504.13123","title":"Low-hallucination Synthetic Captions for Large-Scale Vision-Language Model Pre-training","created":"2025-04-17","cited_by_count":5,"area":"mllm"}],"next_cursor":"100"}