{"total":29,"rows":[{"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":"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":"2312.02949","title":"LLaVA-Grounding: Grounded Visual Chat with Large Multimodal Models","created":"2023-12-05","cited_by_count":113,"area":"mllm"},{"id":"2304.05653","title":"A Closer Look at the Explainability of Contrastive Language-Image Pre-training","created":"2023-04-12","cited_by_count":96,"area":"mllm"},{"id":"2407.08268","title":"Explore the Potential of CLIP for Training-Free Open Vocabulary Semantic Segmentation","created":"2024-07-11","cited_by_count":61,"area":"mllm"},{"id":"2409.15310","title":"Visual Prompting in Multimodal Large Language Models: A Survey","created":"2024-09-05","cited_by_count":54,"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":"2504.11195","title":"R-TPT: Improving Adversarial Robustness of Vision-Language Models through Test-Time Prompt Tuning","created":"2025-04-15","cited_by_count":33,"area":"mllm"},{"id":"2402.11248","title":"CoLLaVO: Crayon Large Language and Vision mOdel","created":"2024-02-17","cited_by_count":26,"area":"mllm"},{"id":"2309.13505","title":"Rewrite Caption Semantics: Bridging Semantic Gaps for Language-Supervised Semantic Segmentation","created":"2023-09-24","cited_by_count":21,"area":"mllm"},{"id":"2407.11213","title":"OpenPSG: Open-set Panoptic Scene Graph Generation via Large Multimodal Models","created":"2024-07-15","cited_by_count":16,"area":"mllm"},{"id":"2410.15364","title":"Scene Graph Generation with Role-Playing Large Language Models","created":"2024-10-20","cited_by_count":16,"area":"mllm"},{"id":"2311.17095","title":"Emergent Open-Vocabulary Semantic Segmentation from Off-the-shelf Vision-Language Models","created":"2023-11-28","cited_by_count":15,"area":"mllm"},{"id":"2502.04981","title":"AutoOcc: Automatic Open-Ended Semantic Occupancy Annotation via Vision-Language Guided Gaussian Splatting","created":"2025-02-07","cited_by_count":14,"area":"mllm"},{"id":"2503.16707","title":"Cross-Modal and Uncertainty-Aware Agglomeration for Open-Vocabulary 3D Scene Understanding","created":"2025-03-20","cited_by_count":13,"area":"mllm"},{"id":"2504.09480","title":"Vision-Language Model for Object Detection and Segmentation: A Review and Evaluation","created":"2025-04-13","cited_by_count":10,"area":"mllm"},{"id":"2409.08468","title":"Generalization Boosted Adapter for Open-Vocabulary Segmentation","created":"2024-09-13","cited_by_count":9,"area":"mllm"},{"id":"2410.08209","title":"Emergent Visual Grounding in Large Multimodal Models Without Grounding Supervision","created":"2024-10-10","cited_by_count":9,"area":"mllm"},{"id":"2507.17436","title":"Dynamic-DINO: Fine-Grained Mixture of Experts Tuning for Real-time Open-Vocabulary Object Detection","created":"2025-07-23","cited_by_count":8,"area":"mllm"},{"id":"2403.09593","title":"Renovating Names in Open-Vocabulary Segmentation Benchmarks","created":"2024-03-14","cited_by_count":7,"area":"mllm"},{"id":"2507.07605","title":"LOSC: LiDAR Open-voc Segmentation Consolidator","created":"2025-07-10","cited_by_count":5,"area":"mllm"},{"id":"2510.22785","title":"Self-Calibrated Consistency can Fight Back for Adversarial Robustness in Vision-Language Models","created":"2025-10-26","cited_by_count":3,"area":"mllm"},{"id":"2511.08173","title":"VLMDiff: Leveraging Vision-Language Models for Multi-Class Anomaly Detection with Diffusion","created":"2025-11-11","cited_by_count":3,"area":"mllm"},{"id":"2505.18819","title":"Parameter-Efficient CLIP Adaptation for 3D Understanding via Unified Tokenization","created":"2025-05-24","cited_by_count":1,"area":"mllm"},{"id":"2508.17846","title":"Alternating Training-based Label Smoothing Enhances Prompt Generalization","created":"2025-08-25","cited_by_count":1,"area":"mllm"},{"id":"2405.01040","title":"Few Shot Class Incremental Learning using Vision-Language models","created":"2024-05-02","cited_by_count":0,"area":"mllm"},{"id":"2512.07360","title":"Structure-Aware Feature Rectification with Region Adjacency Graphs for Training-Free Open-Vocabulary Semantic Segmentation","created":"2025-12-08","cited_by_count":0,"area":"mllm"},{"id":"2602.04699","title":"Annotation Free Spacecraft Detection and Segmentation using Vision Language Models","created":"2026-02-04","cited_by_count":0,"area":"mllm"},{"id":"2605.25922","title":"Closed-Loop Bidirectional Prompting for Adversarial Robustness of Vision Language Models","created":"2026-05-25","cited_by_count":0,"area":"mllm"}],"next_cursor":null}