{"total":55,"rows":[{"id":"2306.14824","title":"Kosmos-2: Grounding Multimodal Large Language Models to the World","created":"2023-06-26","cited_by_count":1089,"area":"mllm"},{"id":"2311.12793","title":"ShareGPT4V: Improving Large Multi-Modal Models with Better Captions","created":"2023-11-21","cited_by_count":1005,"area":"mllm"},{"id":"2310.07704","title":"Ferret: Refer and Ground Anything Anywhere at Any Granularity","created":"2023-10-11","cited_by_count":509,"area":"mllm"},{"id":"2306.09683","title":"Scaling Open-Vocabulary Object Detection","created":"2023-06-16","cited_by_count":343,"area":"mllm"},{"id":"2401.16420","title":"InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model","created":"2024-01-29","cited_by_count":326,"area":"mllm"},{"id":"2302.14115","title":"Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning","created":"2023-02-27","cited_by_count":263,"area":"mllm"},{"id":"2408.16500","title":"CogVLM2: Visual Language Models for Image and Video Understanding","created":"2024-08-29","cited_by_count":217,"area":"mllm"},{"id":"2312.14115","title":"LingoQA: Visual Question Answering for Autonomous Driving","created":"2023-12-21","cited_by_count":145,"area":"mllm"},{"id":"2210.09263","title":"Vision-Language Pre-training: Basics, Recent Advances, and Future Trends","created":"2022-10-17","cited_by_count":117,"area":"mllm"},{"id":"2312.02949","title":"LLaVA-Grounding: Grounded Visual Chat with Large Multimodal Models","created":"2023-12-05","cited_by_count":113,"area":"mllm"},{"id":"2305.18279","title":"Contextual Object Detection with Multimodal Large Language Models","created":"2023-05-29","cited_by_count":100,"area":"mllm"},{"id":"2210.09996","title":"Perceptual Grouping in Contrastive Vision-Language Models","created":"2022-10-18","cited_by_count":82,"area":"mllm"},{"id":"2410.06912","title":"Compositional Entailment Learning for Hyperbolic Vision-Language Models","created":"2024-10-09","cited_by_count":74,"area":"mllm"},{"id":"2310.13355","title":"SILC: Improving Vision Language Pretraining with Self-Distillation","created":"2023-10-20","cited_by_count":66,"area":"mllm"},{"id":"2403.02325","title":"Contrastive Region Guidance: Improving Grounding in Vision-Language Models without Training","created":"2024-03-04","cited_by_count":64,"area":"mllm"},{"id":"2305.03689","title":"COLA: A Benchmark for Compositional Text-to-image Retrieval","created":"2023-05-05","cited_by_count":53,"area":"mllm"},{"id":"2410.12332","title":"MC-Bench: A Benchmark for Multi-Context Visual Grounding in the Era of MLLMs","created":"2024-10-16","cited_by_count":39,"area":"mllm"},{"id":"2410.02746","title":"Contrastive Localized Language-Image Pre-Training","created":"2024-10-03","cited_by_count":33,"area":"mllm"},{"id":"2311.14552","title":"Griffon: Spelling out All Object Locations at Any Granularity with Large Language Models","created":"2023-11-24","cited_by_count":31,"area":"mllm"},{"id":"2311.17518","title":"The devil is in the fine-grained details: Evaluating open-vocabulary object detectors for fine-grained understanding","created":"2023-11-29","cited_by_count":29,"area":"mllm"},{"id":"2312.04016","title":"PartDistill: 3D Shape Part Segmentation by Vision-Language Model Distillation","created":"2023-12-07","cited_by_count":28,"area":"mllm"},{"id":"2303.02489","title":"CapDet: Unifying Dense Captioning and Open-World Detection Pretraining","created":"2023-03-04","cited_by_count":26,"area":"mllm"},{"id":"2210.04135","title":"VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment","created":"2022-10-09","cited_by_count":20,"area":"mllm"},{"id":"2503.17782","title":"GOAL: Global-local Object Alignment Learning","created":"2025-03-22","cited_by_count":17,"area":"mllm"},{"id":"2303.09252","title":"GridCLIP: One-Stage Object Detection by Grid-Level CLIP Representation Learning","created":"2023-03-16","cited_by_count":15,"area":"mllm"},{"id":"2402.08657","title":"PIN: Positional Insert Unlocks Object Localisation Abilities in VLMs","created":"2024-02-13","cited_by_count":14,"area":"mllm"},{"id":"2508.19294","title":"Object Detection with Multimodal Large Vision-Language Models: An In-depth Review","created":"2025-08-25","cited_by_count":14,"area":"mllm"},{"id":"2401.06397","title":"UMG-CLIP: A Unified Multi-Granularity Vision Generalist for Open-World Understanding","created":"2024-01-12","cited_by_count":13,"area":"mllm"},{"id":"2403.03346","title":"Enhancing Vision-Language Pre-training with Rich Supervisions","created":"2024-03-05","cited_by_count":13,"area":"mllm"},{"id":"2308.02982","title":"Beyond First Impressions: Integrating Joint Multi-modal Cues for Comprehensive 3D Representation","created":"2023-08-06","cited_by_count":12,"area":"mllm"},{"id":"2312.01522","title":"G2D: From Global to Dense Radiography Representation Learning via Vision-Language Pre-training","created":"2023-12-03","cited_by_count":12,"area":"mllm"},{"id":"2407.21465","title":"MarvelOVD: Marrying Object Recognition and Vision-Language Models for Robust Open-Vocabulary Object Detection","created":"2024-07-31","cited_by_count":11,"area":"mllm"},{"id":"2507.22431","title":"HQ-CLIP: Leveraging Large Vision-Language Models to Create High-Quality Image-Text Datasets and CLIP Models","created":"2025-07-30","cited_by_count":11,"area":"mllm"},{"id":"2403.18260","title":"Toward Interactive Regional Understanding in Vision-Large Language Models","created":"2024-03-27","cited_by_count":9,"area":"mllm"},{"id":"2412.06244","title":"Unbiased Region-Language Alignment for Open-Vocabulary Dense Prediction","created":"2024-12-09","cited_by_count":9,"area":"mllm"},{"id":"2305.14676","title":"GRILL: Grounded Vision-language Pre-training via Aligning Text and Image Regions","created":"2023-05-24","cited_by_count":8,"area":"mllm"},{"id":"2404.13425","title":"Enhancing Adversarial Robustness of Vision-Language Models through Low-Rank Adaptation","created":"2024-04-20","cited_by_count":8,"area":"mllm"},{"id":"2211.11492","title":"ClipCrop: Conditioned Cropping Driven by Vision-Language Model","created":"2022-11-21","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":"2308.16689","title":"ViLTA: Enhancing Vision-Language Pre-training through Textual Augmentation","created":"2023-08-31","cited_by_count":6,"area":"mllm"},{"id":"2411.18207","title":"From Open Vocabulary to Open World: Teaching Vision Language Models to Detect Novel Objects","created":"2024-11-27","cited_by_count":5,"area":"mllm"},{"id":"2410.14340","title":"Zero-shot Action Localization via the Confidence of Large Vision-Language Models","created":"2024-10-18","cited_by_count":4,"area":"mllm"},{"id":"2309.16552","title":"Semantic Scene Difference Detection in Daily Life Patroling by Mobile Robots using Pre-Trained Large-Scale Vision-Language Model","created":"2023-09-28","cited_by_count":3,"area":"mllm"},{"id":"2508.05323","title":"Textual Inversion for Efficient Adaptation of Open-Vocabulary Object Detectors Without Forgetting","created":"2025-08-07","cited_by_count":3,"area":"mllm"},{"id":"2310.14108","title":"CLIP meets Model Zoo Experts: Pseudo-Supervision for Visual Enhancement","created":"2023-10-21","cited_by_count":2,"area":"mllm"},{"id":"2409.14215","title":"@Bench: Benchmarking Vision-Language Models for Human-centered Assistive Technology","created":"2024-09-21","cited_by_count":2,"area":"mllm"},{"id":"2508.08066","title":"ExpVG: Investigating the Design Space of Visual Grounding in Multimodal Large Language Model","created":"2025-08-11","cited_by_count":2,"area":"mllm"},{"id":"2303.10093","title":"Investigating the Role of Attribute Context in Vision-Language Models for Object Recognition and Detection","created":"2023-03-17","cited_by_count":0,"area":"mllm"},{"id":"2305.18993","title":"ConES: Concept Embedding Search for Parameter Efficient Tuning Large Vision Language Models","created":"2023-05-30","cited_by_count":0,"area":"mllm"},{"id":"2404.10357","title":"Optimization of Prompt Learning via Multi-Knowledge Representation for Vision-Language Models","created":"2024-04-16","cited_by_count":0,"area":"mllm"},{"id":"2407.13368","title":"Affordance Perception by a Knowledge-Guided Vision-Language Model with Efficient Error Correction","created":"2024-07-18","cited_by_count":0,"area":"mllm"},{"id":"2409.16136","title":"HA-FGOVD: Highlighting Fine-grained Attributes via Explicit Linear Composition for Open-Vocabulary Object Detection","created":"2024-09-24","cited_by_count":0,"area":"mllm"},{"id":"2605.26615","title":"FAST-GOAL: Fast and Efficient Global-local Object Alignment Learning","created":"2026-05-26","cited_by_count":0,"area":"mllm"},{"id":"2606.11546","title":"VL-DINO: Leveraging CLIP Vision-Language Knowledge for Open-Vocabulary Object Detectio","created":"2026-06-10","cited_by_count":0,"area":"mllm"},{"id":"2607.09008","title":"C-GAP: Class-Aware and Online Prompting Improves Vision-Language Models on Imbalanced Classes","created":"2026-07-10","cited_by_count":0,"area":"mllm"}],"next_cursor":null}