{"total":348,"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":"2403.20330","title":"Are We on the Right Way for Evaluating Large Vision-Language Models?","created":"2024-03-29","cited_by_count":914,"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":"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":"2405.02246","title":"What matters when building vision-language models?","created":"2024-05-03","cited_by_count":326,"area":"mllm"},{"id":"2408.13257","title":"MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?","created":"2024-08-23","cited_by_count":292,"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":"2504.05299","title":"SmolVLM: Redefining small and efficient multimodal models","created":"2025-04-07","cited_by_count":237,"area":"mllm"},{"id":"2406.18521","title":"CharXiv: Charting Gaps in Realistic Chart Understanding in Multimodal LLMs","created":"2024-06-26","cited_by_count":234,"area":"mllm"},{"id":"2501.01957","title":"VITA-1.5: Towards GPT-4o Level Real-Time Vision and Speech Interaction","created":"2025-01-03","cited_by_count":197,"area":"mllm"},{"id":"2408.05211","title":"VITA: Towards Open-Source Interactive Omni Multimodal LLM","created":"2024-08-09","cited_by_count":173,"area":"mllm"},{"id":"2408.12637","title":"Building and better understanding vision-language models: insights and future directions","created":"2024-08-22","cited_by_count":173,"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":"2407.02392","title":"TokenPacker: Efficient Visual Projector for Multimodal LLM","created":"2024-07-02","cited_by_count":172,"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":"2502.04326","title":"WorldSense: Evaluating Real-world Omnimodal Understanding for Multimodal LLMs","created":"2025-02-06","cited_by_count":155,"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":"2411.16044","title":"ZoomEye: Enhancing Multimodal LLMs with Human-Like Zooming Capabilities through Tree-Based Image Exploration","created":"2024-11-25","cited_by_count":103,"area":"mllm"},{"id":"2409.15272","title":"OmniBench: Towards The Future of Universal Omni-Language Models","created":"2024-09-23","cited_by_count":102,"area":"mllm"},{"id":"2404.05955","title":"VisualWebBench: How Far Have Multimodal LLMs Evolved in Web Page Understanding and Grounding?","created":"2024-04-09","cited_by_count":100,"area":"mllm"},{"id":"2410.14669","title":"NaturalBench: Evaluating Vision-Language Models on Natural Adversarial Samples","created":"2024-10-18","cited_by_count":97,"area":"mllm"},{"id":"2405.10739","title":"Efficient Multimodal Large Language Models: A Survey","created":"2024-05-17","cited_by_count":96,"area":"mllm"},{"id":"2408.03361","title":"GMAI-MMBench: A Comprehensive Multimodal Evaluation Benchmark Towards General Medical AI","created":"2024-08-06","cited_by_count":96,"area":"mllm"},{"id":"2406.11832","title":"Unveiling Encoder-Free Vision-Language Models","created":"2024-06-17","cited_by_count":94,"area":"mllm"},{"id":"2410.16261","title":"Mini-InternVL: A Flexible-Transfer Pocket Multimodal Model with 5% Parameters and 90% Performance","created":"2024-10-21","cited_by_count":94,"area":"mllm"},{"id":"2501.06598","title":"ChartCoder: Advancing Multimodal Large Language Model for Chart-to-Code Generation","created":"2025-01-11","cited_by_count":92,"area":"mllm"},{"id":"2406.11833","title":"MMDU: A Multi-Turn Multi-Image Dialog Understanding Benchmark and Instruction-Tuning Dataset for LVLMs","created":"2024-06-17","cited_by_count":90,"area":"mllm"},{"id":"2410.11779","title":"MLLM can see? Dynamic Correction Decoding for Hallucination Mitigation","created":"2024-10-15","cited_by_count":88,"area":"mllm"},{"id":"2502.10391","title":"MM-RLHF: The Next Step Forward in Multimodal LLM Alignment","created":"2025-02-14","cited_by_count":83,"area":"mllm"},{"id":"2503.06287","title":"Your Large Vision-Language Model Only Needs A Few Attention Heads For Visual Grounding","created":"2025-03-08","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":"2409.20566","title":"MM1.5: Methods, Analysis & Insights from Multimodal LLM Fine-tuning","created":"2024-09-30","cited_by_count":76,"area":"mllm"},{"id":"2408.02718","title":"MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models","created":"2024-08-05","cited_by_count":67,"area":"mllm"},{"id":"2411.02937","title":"Benchmarking Multimodal Retrieval Augmented Generation with Dynamic VQA Dataset and Self-adaptive Planning Agent","created":"2024-11-05","cited_by_count":65,"area":"mllm"},{"id":"2410.09855","title":"Text4Seg: Reimagining Image Segmentation as Text Generation","created":"2024-10-13","cited_by_count":61,"area":"mllm"},{"id":"2408.16730","title":"VideoLLM-MoD: Efficient Video-Language Streaming with Mixture-of-Depths Vision Computation","created":"2024-08-29","cited_by_count":55,"area":"mllm"},{"id":"2410.09575","title":"Reconstructive Visual Instruction Tuning","created":"2024-10-12","cited_by_count":55,"area":"mllm"},{"id":"2505.17015","title":"Multi-SpatialMLLM: Multi-Frame Spatial Understanding with Multi-Modal Large Language Models","created":"2025-05-22","cited_by_count":52,"area":"mllm"},{"id":"2407.12709","title":"MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models","created":"2024-07-17","cited_by_count":46,"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":"2408.15881","title":"LLaVA-MoD: Making LLaVA Tiny via MoE Knowledge Distillation","created":"2024-08-28","cited_by_count":45,"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":"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":"2502.06788","title":"EVEv2: Improved Baselines for Encoder-Free Vision-Language Models","created":"2025-02-10","cited_by_count":41,"area":"mllm"},{"id":"2503.06486","title":"PerturboLLaVA: Reducing Multimodal Hallucinations with Perturbative Visual Training","created":"2025-03-09","cited_by_count":38,"area":"mllm"},{"id":"2406.09367","title":"Needle In A Video Haystack: A Scalable Synthetic Evaluator for Video MLLMs","created":"2024-06-13","cited_by_count":37,"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":"2501.02765","title":"Visual Large Language Models for Generalized and Specialized Applications","created":"2025-01-06","cited_by_count":36,"area":"mllm"},{"id":"2406.11503","title":"GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation","created":"2024-06-17","cited_by_count":32,"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":"2410.05261","title":"TextHawk2: A Large Vision-Language Model Excels in Bilingual OCR and Grounding with 16x Fewer Tokens","created":"2024-10-07","cited_by_count":32,"area":"mllm"},{"id":"2406.02539","title":"Parrot: Multilingual Visual Instruction Tuning","created":"2024-06-04","cited_by_count":30,"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":"2410.05474","title":"R-Bench: Are your Large Multimodal Model Robust to Real-world Corruptions?","created":"2024-10-07","cited_by_count":30,"area":"mllm"},{"id":"2501.03225","title":"Automated Generation of Challenging Multiple-Choice Questions for Vision Language Model Evaluation","created":"2025-01-06","cited_by_count":30,"area":"mllm"},{"id":"2502.11051","title":"MMUnlearner: Reformulating Multimodal Machine Unlearning in the Era of Multimodal Large Language Models","created":"2025-02-16","cited_by_count":30,"area":"mllm"},{"id":"2503.14607","title":"Can Large Vision Language Models Read Maps Like a Human?","created":"2025-03-18","cited_by_count":30,"area":"mllm"},{"id":"2502.13146","title":"Re-Align: Aligning Vision Language Models via Retrieval-Augmented Direct Preference Optimization","created":"2025-02-18","cited_by_count":29,"area":"mllm"},{"id":"2505.10610","title":"MMLongBench: Benchmarking Long-Context Vision-Language Models Effectively and Thoroughly","created":"2025-05-15","cited_by_count":29,"area":"mllm"},{"id":"2412.00832","title":"EventGPT: Event Stream Understanding with Multimodal Large Language Models","created":"2024-12-01","cited_by_count":28,"area":"mllm"},{"id":"2412.09616","title":"V2PE: Improving Multimodal Long-Context Capability of Vision-Language Models with Variable Visual Position Encoding","created":"2024-12-12","cited_by_count":28,"area":"mllm"},{"id":"2503.15621","title":"LLaVA-MORE: A Comparative Study of LLMs and Visual Backbones for Enhanced Visual Instruction Tuning","created":"2025-03-19","cited_by_count":28,"area":"mllm"},{"id":"2411.00997","title":"Identifying Implicit Social Biases in Vision-Language Models","created":"2024-11-01","cited_by_count":27,"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":"2406.14194","title":"VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model","created":"2024-06-20","cited_by_count":26,"area":"mllm"},{"id":"2408.02034","title":"Mini-Monkey: Alleviating the Semantic Sawtooth Effect for Lightweight MLLMs via Complementary Image Pyramid","created":"2024-08-04","cited_by_count":26,"area":"mllm"},{"id":"2410.07113","title":"Personalized Visual Instruction Tuning","created":"2024-10-09","cited_by_count":24,"area":"mllm"},{"id":"2410.14179","title":"MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart Problems","created":"2024-10-18","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":"2504.08358","title":"LMM4LMM: Benchmarking and Evaluating Large-multimodal Image Generation with LMMs","created":"2025-04-11","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":"2410.11829","title":"MMFuser: Multimodal Multi-Layer Feature Fuser for Fine-Grained Vision-Language Understanding","created":"2024-10-15","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":"2407.14439","title":"Token-level Correlation-guided Compression for Efficient Multimodal Document Understanding","created":"2024-07-19","cited_by_count":22,"area":"mllm"},{"id":"2410.08695","title":"Dynamic Multimodal Evaluation with Flexible Complexity by Vision-Language Bootstrapping","created":"2024-10-11","cited_by_count":22,"area":"mllm"},{"id":"2412.01175","title":"OBI-Bench: Can LMMs Aid in Study of Ancient Script on Oracle Bones?","created":"2024-12-02","cited_by_count":22,"area":"mllm"},{"id":"2503.06063","title":"Multi-Layer Visual Feature Fusion in Multimodal LLMs: Methods, Analysis, and Best Practices","created":"2025-03-08","cited_by_count":22,"area":"mllm"},{"id":"2410.04521","title":"MC-CoT: A Modular Collaborative CoT Framework for Zero-shot Medical-VQA with LLM and MLLM Integration","created":"2024-10-06","cited_by_count":21,"area":"mllm"},{"id":"2503.21307","title":"InternVL-X: Advancing and Accelerating InternVL Series with Efficient Visual Token Compression","created":"2025-03-27","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":"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":"2501.16297","title":"FALCON: Resolving Visual Redundancy and Fragmentation in High-resolution Multimodal Large Language Models via Visual Registers","created":"2025-01-27","cited_by_count":20,"area":"mllm"},{"id":"2510.08510","title":"To Sink or Not to Sink: Visual Information Pathways in Large Vision-Language Models","created":"2025-10-09","cited_by_count":20,"area":"mllm"},{"id":"2405.20339","title":"Visual Perception by Large Language Model's Weights","created":"2024-05-30","cited_by_count":19,"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":"2502.01977","title":"AutoGUI: Scaling GUI Grounding with Automatic Functionality Annotations from LLMs","created":"2025-02-04","cited_by_count":19,"area":"mllm"},{"id":"2503.02358","title":"Are Large Vision Language Models Good Game Players?","created":"2025-03-04","cited_by_count":19,"area":"mllm"},{"id":"2505.11454","title":"HumaniBench: A Human-Centric Framework for Large Multimodal Models Evaluation","created":"2025-05-16","cited_by_count":19,"area":"mllm"},{"id":"2408.16357","title":"Law of Vision Representation in MLLMs","created":"2024-08-29","cited_by_count":18,"area":"mllm"},{"id":"2506.01663","title":"Zoom-Refine: Boosting High-Resolution Multimodal Understanding via Localized Zoom and Self-Refinement","created":"2025-06-02","cited_by_count":18,"area":"mllm"},{"id":"2509.09254","title":"Towards Better Dental AI: A Multimodal Benchmark and Instruction Dataset for Panoramic X-ray Analysis","created":"2025-09-11","cited_by_count":18,"area":"mllm"},{"id":"2601.08325","title":"ActiveVLA: Injecting Active Perception into Vision-Language-Action Models for Precise 3D Robotic Manipulation","created":"2026-01-13","cited_by_count":18,"area":"mllm"},{"id":"2602.23699","title":"HiDrop: Hierarchical Vision Token Reduction in MLLMs via Late Injection, Concave Pyramid Pruning, and Early Exit","created":"2026-02-27","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":"2506.09040","title":"Autoregressive Semantic Visual Reconstruction Helps VLMs Understand Better","created":"2025-06-10","cited_by_count":17,"area":"mllm"},{"id":"2403.06728","title":"Multimodal Large Language Model driven Radiology Report Generation with Clinical Knowledge Enhancement","created":"2024-03-11","cited_by_count":16,"area":"mllm"}],"next_cursor":"100"}