{"total":77,"rows":[{"id":"2306.00890","title":"LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day","created":"2023-06-01","cited_by_count":1305,"area":"mllm"},{"id":"2308.02490","title":"MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities","created":"2023-08-04","cited_by_count":1239,"area":"mllm"},{"id":"2306.13549","title":"A Survey on Multimodal Large Language Models","created":"2023-06-23","cited_by_count":909,"area":"mllm"},{"id":"2310.14566","title":"HallusionBench: An Advanced Diagnostic Suite for Entangled Language Hallucination and Visual Illusion in Large Vision-Language Models","created":"2023-10-23","cited_by_count":583,"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":"2401.01614","title":"GPT-4V(ision) is a Generalist Web Agent, if Grounded","created":"2024-01-03","cited_by_count":563,"area":"mllm"},{"id":"2305.03726","title":"Otter: A Multi-Modal Model with In-Context Instruction Tuning","created":"2023-05-05","cited_by_count":550,"area":"mllm"},{"id":"2305.07895","title":"OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models","created":"2023-05-13","cited_by_count":476,"area":"mllm"},{"id":"2310.01412","title":"DriveGPT4: Interpretable End-to-end Autonomous Driving via Large Language Model","created":"2023-10-02","cited_by_count":461,"area":"mllm"},{"id":"2306.14565","title":"Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning","created":"2023-06-26","cited_by_count":445,"area":"mllm"},{"id":"2410.04417","title":"SparseVLM: Visual Token Sparsification for Efficient Vision-Language Model Inference","created":"2024-10-06","cited_by_count":391,"area":"mllm"},{"id":"2404.18930","title":"Hallucination of Multimodal Large Language Models: A Survey","created":"2024-04-29","cited_by_count":388,"area":"mllm"},{"id":"2311.01378","title":"Vision-Language Foundation Models as Effective Robot Imitators","created":"2023-11-02","cited_by_count":349,"area":"mllm"},{"id":"2311.07575","title":"SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models","created":"2023-11-13","cited_by_count":286,"area":"mllm"},{"id":"2306.09265","title":"LVLM-eHub: A Comprehensive Evaluation Benchmark for Large Vision-Language Models","created":"2023-06-15","cited_by_count":217,"area":"mllm"},{"id":"2311.05437","title":"LLaVA-Plus: Learning to Use Tools for Creating Multimodal Agents","created":"2023-11-09","cited_by_count":193,"area":"mllm"},{"id":"2401.16822","title":"EarthGPT: A Universal Multi-modal Large Language Model for Multi-sensor Image Comprehension in Remote Sensing Domain","created":"2024-01-30","cited_by_count":184,"area":"mllm"},{"id":"2402.09181","title":"OmniMedVQA: A New Large-Scale Comprehensive Evaluation Benchmark for Medical LVLM","created":"2024-02-14","cited_by_count":184,"area":"mllm"},{"id":"2407.21771","title":"Paying More Attention to Image: A Training-Free Method for Alleviating Hallucination in LVLMs","created":"2024-07-31","cited_by_count":179,"area":"mllm"},{"id":"2402.17766","title":"ShapeLLM: Universal 3D Object Understanding for Embodied Interaction","created":"2024-02-27","cited_by_count":137,"area":"mllm"},{"id":"2311.13614","title":"HalluciDoctor: Mitigating Hallucinatory Toxicity in Visual Instruction Data","created":"2023-11-22","cited_by_count":126,"area":"mllm"},{"id":"2409.11402","title":"NVLM: Open Frontier-Class Multimodal LLMs","created":"2024-09-17","cited_by_count":125,"area":"mllm"},{"id":"2308.06595","title":"VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use","created":"2023-08-12","cited_by_count":102,"area":"mllm"},{"id":"2308.12714","title":"VIGC: Visual Instruction Generation and Correction","created":"2023-08-24","cited_by_count":80,"area":"mllm"},{"id":"2406.04334","title":"DeepStack: Deeply Stacking Visual Tokens is Surprisingly Simple and Effective for LMMs","created":"2024-06-06","cited_by_count":75,"area":"mllm"},{"id":"2411.15296","title":"MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs","created":"2024-11-22","cited_by_count":72,"area":"mllm"},{"id":"2412.03735","title":"VidHalluc: Evaluating Temporal Hallucinations in Multimodal Large Language Models for Video Understanding","created":"2024-12-04","cited_by_count":68,"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":"2503.12769","title":"ViSpeak: Visual Instruction Feedback in Streaming Videos","created":"2025-03-17","cited_by_count":42,"area":"mllm"},{"id":"2307.01003","title":"Visual Instruction Tuning with Polite Flamingo","created":"2023-07-03","cited_by_count":38,"area":"mllm"},{"id":"2410.10855","title":"Core Knowledge Deficits in Multi-Modal Language Models","created":"2024-10-06","cited_by_count":38,"area":"mllm"},{"id":"2406.05821","title":"F-LMM: Grounding Frozen Large Multimodal Models","created":"2024-06-09","cited_by_count":34,"area":"mllm"},{"id":"2305.17718","title":"FuseCap: Leveraging Large Language Models for Enriched Fused Image Captions","created":"2023-05-28","cited_by_count":33,"area":"mllm"},{"id":"2308.10253","title":"StableLLaVA: Enhanced Visual Instruction Tuning with Synthesized Image-Dialogue Data","created":"2023-08-20","cited_by_count":33,"area":"mllm"},{"id":"2402.06599","title":"On the Out-Of-Distribution Generalization of Multimodal Large Language Models","created":"2024-02-09","cited_by_count":30,"area":"mllm"},{"id":"2407.01851","title":"Meerkat: Audio-Visual Large Language Model for Grounding in Space and Time","created":"2024-07-01","cited_by_count":26,"area":"mllm"},{"id":"2502.03333","title":"RadVLM: A Multitask Conversational Vision-Language Model for Radiology","created":"2025-02-05","cited_by_count":25,"area":"mllm"},{"id":"2308.07891","title":"Link-Context Learning for Multimodal LLMs","created":"2023-08-15","cited_by_count":24,"area":"mllm"},{"id":"2410.08405","title":"AgroGPT: Efficient Agricultural Vision-Language Model with Expert Tuning","created":"2024-10-10","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":"2502.01419","title":"Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models","created":"2025-02-03","cited_by_count":22,"area":"mllm"},{"id":"2310.05863","title":"Fine-grained Audio-Visual Joint Representations for Multimodal Large Language Models","created":"2023-10-09","cited_by_count":21,"area":"mllm"},{"id":"2306.14895","title":"Large Multimodal Models: Notes on CVPR 2023 Tutorial","created":"2023-06-26","cited_by_count":18,"area":"mllm"},{"id":"2310.04869","title":"ILuvUI: Instruction-tuned LangUage-Vision modeling of UIs from Machine Conversations","created":"2023-10-07","cited_by_count":17,"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":"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":"2503.07591","title":"Filter Images First, Generate Instructions Later: Pre-Instruction Data Selection for Visual Instruction Tuning","created":"2025-03-10","cited_by_count":12,"area":"mllm"},{"id":"2512.04000","title":"Divide, then Ground: Adapting Frame Selection to Query Types for Long-Form Video Understanding","created":"2025-12-03","cited_by_count":11,"area":"mllm"},{"id":"2410.00324","title":"Vision Language Models See What You Want but not What You See","created":"2024-10-01","cited_by_count":10,"area":"mllm"},{"id":"2503.20502","title":"MLLM-Selector: Necessity and Diversity-driven High-Value Data Selection for Enhanced Visual Instruction Tuning","created":"2025-03-26","cited_by_count":9,"area":"mllm"},{"id":"2505.17316","title":"Analyzing Fine-Grained Alignment and Enhancing Vision Understanding in Multimodal Language Models","created":"2025-05-22","cited_by_count":9,"area":"mllm"},{"id":"2311.17647","title":"Text as Images: Can Multimodal Large Language Models Follow Printed Instructions in Pixels?","created":"2023-11-29","cited_by_count":7,"area":"mllm"},{"id":"2403.10492","title":"Mitigating Dialogue Hallucination for Large Vision Language Models via Adversarial Instruction Tuning","created":"2024-03-15","cited_by_count":7,"area":"mllm"},{"id":"2407.17734","title":"Cost-effective Instruction Learning for Pathology Vision and Language Analysis","created":"2024-07-25","cited_by_count":7,"area":"mllm"},{"id":"2502.10273","title":"Probing Perceptual Constancy in Large Vision-Language Models","created":"2025-02-14","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":"2308.12956","title":"DLIP: Distilling Language-Image Pre-training","created":"2023-08-24","cited_by_count":5,"area":"mllm"},{"id":"2312.02233","title":"MedXChat: A Unified Multimodal Large Language Model Framework towards CXRs Understanding and Generation","created":"2023-12-04","cited_by_count":5,"area":"mllm"},{"id":"2411.01846","title":"KptLLM: Unveiling the Power of Large Language Model for Keypoint Comprehension","created":"2024-11-04","cited_by_count":5,"area":"mllm"},{"id":"2502.00954","title":"Hypo3D: Exploring Hypothetical Reasoning in 3D","created":"2025-02-02","cited_by_count":5,"area":"mllm"},{"id":"2410.00332","title":"Vision Language Models Know Law of Conservation without Understanding More-or-Less","created":"2024-10-01","cited_by_count":4,"area":"mllm"},{"id":"2311.07594","title":"How to Bridge the Gap between Modalities: Survey on Multimodal Large Language Model","created":"2023-11-10","cited_by_count":3,"area":"mllm"},{"id":"2406.15768","title":"MR-MLLM: Mutual Reinforcement of Multimodal Comprehension and Vision Perception","created":"2024-06-22","cited_by_count":3,"area":"mllm"},{"id":"2409.13612","title":"FIHA: Autonomous Hallucination Evaluation in Vision-Language Models with Davidson Scene Graphs","created":"2024-09-20","cited_by_count":3,"area":"mllm"},{"id":"2506.16112","title":"AutoV: Loss-Oriented Ranking for Visual Prompt Retrieval in LVLMs","created":"2025-06-19","cited_by_count":2,"area":"mllm"},{"id":"2507.02909","title":"Fine-grained Token Allocation Via Operation Pruning for Efficient MLLMs","created":"2025-06-24","cited_by_count":2,"area":"mllm"},{"id":"2507.19939","title":"LLMControl: Grounded Control of Text-to-Image Diffusion-based Synthesis with Multimodal LLMs","created":"2025-07-26","cited_by_count":2,"area":"mllm"},{"id":"2603.04908","title":"AdaIAT: Adaptively Increasing Attention to Generated Text to Alleviate Hallucinations in LVLM","created":"2026-03-05","cited_by_count":2,"area":"mllm"},{"id":"2512.14102","title":"Neurosymbolic Inference On Foundation Models For Remote Sensing Text-to-image Retrieval With Complex Queries","created":"2025-12-16","cited_by_count":1,"area":"mllm"},{"id":"2506.03614","title":"VLMs Can Aggregate Scattered Training Patches","created":"2025-06-04","cited_by_count":0,"area":"mllm"},{"id":"2507.11102","title":"KptLLM++: Towards Generic Keypoint Comprehension with Large Language Model","created":"2025-07-15","cited_by_count":0,"area":"mllm"},{"id":"2512.08881","title":"SATGround: A Spatially-Aware Approach for Visual Grounding in Remote Sensing","created":"2025-12-09","cited_by_count":0,"area":"mllm"},{"id":"2601.06566","title":"QCaption: Video Captioning and Q&A through Fusion of Large Multimodal Models","created":"2026-01-10","cited_by_count":0,"area":"mllm"},{"id":"2605.14530","title":"Mitigating Mask Prior Drift and Positional Attention Collapse in Large Diffusion Vision-Language Models","created":"2026-05-14","cited_by_count":0,"area":"mllm"},{"id":"2607.10308","title":"Generalize LMMs to Versatile Visual Modalities via Fabricated Modality Synthesis","created":"2026-07-11","cited_by_count":0,"area":"mllm"},{"id":"2609.36440","title":"DARE to Mitigate Hallucination: Dual-path Auto-Regressive-aware Editing","created":"2026-09-29","cited_by_count":0,"area":"mllm"}],"next_cursor":null}