{"total":44,"rows":[{"id":"2304.00685","title":"Vision-Language Models for Vision Tasks: A Survey","created":"2023-04-03","cited_by_count":839,"area":"mllm"},{"id":"2407.12442","title":"ClearCLIP: Decomposing CLIP Representations for Dense Vision-Language Inference","created":"2024-07-17","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":"2305.05726","title":"Vision-Language Models in Remote Sensing: Current Progress and Future Trends","created":"2023-05-09","cited_by_count":93,"area":"mllm"},{"id":"2312.00878","title":"Grounding Everything: Emerging Localization Properties in Vision-Language Transformers","created":"2023-12-01","cited_by_count":91,"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":"2406.11171","title":"SUGARCREPE++ Dataset: Vision-Language Model Sensitivity to Semantic and Lexical Alterations","created":"2024-06-17","cited_by_count":42,"area":"mllm"},{"id":"2411.15869","title":"Self-Calibrated CLIP for Training-Free Open-Vocabulary Segmentation","created":"2024-11-24","cited_by_count":34,"area":"mllm"},{"id":"2411.15851","title":"ResCLIP: Residual Attention for Training-free Dense Vision-language Inference","created":"2024-11-24","cited_by_count":29,"area":"mllm"},{"id":"2409.19846","title":"Towards Open-Vocabulary Semantic Segmentation Without Semantic Labels","created":"2024-09-30","cited_by_count":19,"area":"mllm"},{"id":"2406.00670","title":"Cascade-CLIP: Cascaded Vision-Language Embeddings Alignment for Zero-Shot Semantic Segmentation","created":"2024-06-02","cited_by_count":17,"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":"2409.06809","title":"DetailCLIP: Detail-Oriented CLIP for Fine-Grained Tasks","created":"2024-09-10","cited_by_count":15,"area":"mllm"},{"id":"2505.24693","title":"Conformal Prediction for Zero-Shot Models","created":"2025-05-30","cited_by_count":15,"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":"2310.17218","title":"Prototypical Contrastive Learning-based CLIP Fine-tuning for Object Re-identification","created":"2023-10-26","cited_by_count":11,"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":"2506.06076","title":"Full Conformal Adaptation of Medical Vision-Language Models","created":"2025-06-06","cited_by_count":9,"area":"mllm"},{"id":"2508.00557","title":"Training-Free Class Purification for Open-Vocabulary Semantic Segmentation","created":"2025-08-01","cited_by_count":9,"area":"mllm"},{"id":"2403.06453","title":"FontCLIP: A Semantic Typography Visual-Language Model for Multilingual Font Applications","created":"2024-03-11","cited_by_count":8,"area":"mllm"},{"id":"2411.12044","title":"ITACLIP: Boosting Training-Free Semantic Segmentation with Image, Text, and Architectural Enhancements","created":"2024-11-18","cited_by_count":7,"area":"mllm"},{"id":"2403.08426","title":"Language-Driven Visual Consensus for Zero-Shot Semantic Segmentation","created":"2024-03-13","cited_by_count":6,"area":"mllm"},{"id":"2312.14149","title":"TagAlign: Improving Vision-Language Alignment with Multi-Tag Classification","created":"2023-12-21","cited_by_count":5,"area":"mllm"},{"id":"2412.11464","title":"High-Quality Mask Tuning Matters for Open-Vocabulary Segmentation","created":"2024-12-16","cited_by_count":5,"area":"mllm"},{"id":"2503.01263","title":"Generalizable Prompt Learning of CLIP: A Brief Overview","created":"2025-03-03","cited_by_count":3,"area":"mllm"},{"id":"2407.05061","title":"Test-time Contrastive Concepts for Open-world Semantic Segmentation with Vision-Language Models","created":"2024-07-06","cited_by_count":2,"area":"mllm"},{"id":"2407.19674","title":"Advancing Prompt Learning through an External Layer","created":"2024-07-29","cited_by_count":2,"area":"mllm"},{"id":"2501.06031","title":"Generate, Transduct, Adapt: Iterative Transduction with VLMs","created":"2025-01-10","cited_by_count":2,"area":"mllm"},{"id":"2506.08678","title":"ATAS: Any-to-Any Self-Distillation for Enhanced Open-Vocabulary Dense Prediction","created":"2025-06-10","cited_by_count":2,"area":"mllm"},{"id":"2509.23917","title":"Bridging the Task Gap: Multi-Task Adversarial Transferability in CLIP and Its Derivatives","created":"2025-09-28","cited_by_count":2,"area":"mllm"},{"id":"2602.17799","title":"Enabling Training-Free Text-Based Remote Sensing Segmentation","created":"2026-02-19","cited_by_count":2,"area":"mllm"},{"id":"2603.21386","title":"Mitigating Objectness Bias and Region-to-Text Misalignment for Open-Vocabulary Panoptic Segmentation","created":"2026-03-22","cited_by_count":2,"area":"mllm"},{"id":"2312.00663","title":"Generalized Robot 3D Vision-Language Model with Fast Rendering and Pre-Training Vision-Language Alignment","created":"2023-12-01","cited_by_count":1,"area":"mllm"},{"id":"2504.12436","title":"Sparsity Outperforms Low-Rank Projections in Few-Shot Adaptation","created":"2025-04-16","cited_by_count":1,"area":"mllm"},{"id":"2505.05318","title":"Mapping User Trust in Vision Language Models: Research Landscape, Challenges, and Prospects","created":"2025-05-08","cited_by_count":1,"area":"mllm"},{"id":"2509.11840","title":"Synthetic Captions for Open-Vocabulary Zero-Shot Segmentation","created":"2025-09-15","cited_by_count":1,"area":"mllm"},{"id":"2509.00598","title":"DGL-RSIS: Decoupling Global Spatial Context and Local Class Semantics for Training-Free Remote Sensing Image Segmentation","created":"2025-08-30","cited_by_count":0,"area":"mllm"},{"id":"2511.13458","title":"Trust in Vision-Language Models: Insights from a Participatory User Workshop","created":"2025-11-17","cited_by_count":0,"area":"mllm"},{"id":"2512.02566","title":"From Panel to Pixel: Zoom-In Vision-Language Pretraining from Biomedical Scientific Literature","created":"2025-12-02","cited_by_count":0,"area":"mllm"},{"id":"2602.23339","title":"Retrieve and Segment: Are a Few Examples Enough to Bridge the Supervision Gap in Open-Vocabulary Segmentation?","created":"2026-02-26","cited_by_count":0,"area":"mllm"},{"id":"2604.08110","title":"OV-Stitcher: A Global Context-Aware Framework for Training-Free Open-Vocabulary Semantic Segmentation","created":"2026-04-09","cited_by_count":0,"area":"mllm"},{"id":"2604.08956","title":"Low-Data Supervised Adaptation Outperforms Prompting for Cloud Segmentation Under Domain Shift","created":"2026-04-10","cited_by_count":0,"area":"mllm"}],"next_cursor":null}