{"total":15,"rows":[{"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":"2306.07282","title":"Waffling around for Performance: Visual Classification with Random Words and Broad Concepts","created":"2023-06-12","cited_by_count":101,"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":"2402.11248","title":"CoLLaVO: Crayon Large Language and Vision mOdel","created":"2024-02-17","cited_by_count":26,"area":"mllm"},{"id":"2405.01468","title":"Understanding Retrieval-Augmented Task Adaptation for Vision-Language Models","created":"2024-05-02","cited_by_count":10,"area":"mllm"},{"id":"2501.13982","title":"Attribute-based Visual Reprogramming for Vision-Language Models","created":"2025-01-23","cited_by_count":8,"area":"mllm"},{"id":"2409.01821","title":"When Does Visual Prompting Outperform Linear Probing for Vision-Language Models? A Likelihood Perspective","created":"2024-09-03","cited_by_count":1,"area":"mllm"},{"id":"2501.00457","title":"Differentiable Prompt Learning for Vision Language Models","created":"2024-12-31","cited_by_count":1,"area":"mllm"},{"id":"2506.04005","title":"Vocabulary-free few-shot learning for Vision-Language Models","created":"2025-06-04","cited_by_count":1,"area":"mllm"},{"id":"2606.20244","title":"SPOT-E: Test-Time Entropy Shaping with Visual Spotlights for Frozen VLMs","created":"2026-06-18","cited_by_count":1,"area":"mllm"},{"id":"2312.10945","title":"LaViP:Language-Grounded Visual Prompts","created":"2023-12-18","cited_by_count":0,"area":"mllm"},{"id":"2507.14686","title":"From Semantics, Scene to Instance-awareness: Distilling Foundation Model for Grounded Open-vocabulary Situation Recognition","created":"2025-07-19","cited_by_count":0,"area":"mllm"},{"id":"2605.08902","title":"DAPE: Dynamic Non-uniform Alignment and Progressive Detail Enhancement Techniques for Improving the Performance of Efficient Visual Language Models","created":"2026-05-09","cited_by_count":0,"area":"mllm"},{"id":"2606.24740","title":"BioMedVR: Confusion-Aware Mixture-of-Prompt Experts for Biomedical Visual Reprogramming","created":"2026-06-23","cited_by_count":0,"area":"mllm"},{"id":"2609.36680","title":"Reprogramming Vision-Language Models via Structured Prompt Reparameterization","created":"2026-09-29","cited_by_count":0,"area":"mllm"}],"next_cursor":null}