{"total":20,"rows":[{"id":"2404.00851","title":"Prompt Learning via Meta-Regularization","created":"2024-04-01","cited_by_count":26,"area":"mllm"},{"id":"2304.04512","title":"Defense-Prefix for Preventing Typographic Attacks on CLIP","created":"2023-04-10","cited_by_count":24,"area":"mllm"},{"id":"2412.00114","title":"SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments","created":"2024-11-28","cited_by_count":22,"area":"mllm"},{"id":"2304.03659","title":"Probing Conceptual Understanding of Large Visual-Language Models","created":"2023-04-07","cited_by_count":17,"area":"mllm"},{"id":"2312.00096","title":"OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognition","created":"2023-11-30","cited_by_count":16,"area":"mllm"},{"id":"2405.13777","title":"No Filter: Cultural and Socioeconomic Diversity in Contrastive Vision-Language Models","created":"2024-05-22","cited_by_count":16,"area":"mllm"},{"id":"2406.00345","title":"DeCoOp: Robust Prompt Tuning with Out-of-Distribution Detection","created":"2024-06-01","cited_by_count":14,"area":"mllm"},{"id":"2506.02041","title":"Enhancing Multimodal Continual Instruction Tuning with BranchLoRA","created":"2025-05-31","cited_by_count":14,"area":"mllm"},{"id":"2504.04893","title":"SCAM: A Real-World Typographic Robustness Evaluation for Multimodal Foundation Models","created":"2025-04-07","cited_by_count":13,"area":"mllm"},{"id":"2402.15021","title":"CLoVe: Encoding Compositional Language in Contrastive Vision-Language Models","created":"2024-02-22","cited_by_count":12,"area":"mllm"},{"id":"2305.14053","title":"Parts of Speech-Grounded Subspaces in Vision-Language Models","created":"2023-05-23","cited_by_count":11,"area":"mllm"},{"id":"2312.06112","title":"MAFA: Managing False Negatives for Vision-Language Pre-training","created":"2023-12-11","cited_by_count":11,"area":"mllm"},{"id":"2212.04412","title":"Task Bias in Vision-Language Models","created":"2022-12-08","cited_by_count":8,"area":"mllm"},{"id":"2307.00398","title":"ProbVLM: Probabilistic Adapter for Frozen Vision-Language Models","created":"2023-07-01","cited_by_count":7,"area":"mllm"},{"id":"2505.19373","title":"DiSa: Directional Saliency-Aware Prompt Learning for Generalizable Vision-Language Models","created":"2025-05-26","cited_by_count":4,"area":"mllm"},{"id":"2507.13089","title":"GLAD: Generalizable Tuning for Vision-Language Models","created":"2025-07-17","cited_by_count":3,"area":"mllm"},{"id":"2305.02297","title":"Making the Most of What You Have: Adapting Pre-trained Visual Language Models in the Low-data Regime","created":"2023-05-03","cited_by_count":1,"area":"mllm"},{"id":"2408.09706","title":"MePT: Multi-Representation Guided Prompt Tuning for Vision-Language Model","created":"2024-08-19","cited_by_count":1,"area":"mllm"},{"id":"2604.04473","title":"Beyond Standard Benchmarks: A Systematic Audit of Vision-Language Model's Robustness to Natural Semantic Variation Across Diverse Tasks","created":"2026-04-06","cited_by_count":0,"area":"mllm"},{"id":"2607.02494","title":"Towards Robustness against Typographic Attack with Training-free Concept Localization","created":"2026-07-02","cited_by_count":0,"area":"mllm"}],"next_cursor":null}