{"total":22,"rows":[{"id":"2405.02266","title":"On the test-time zero-shot generalization of vision-language models: Do we really need prompt learning?","created":"2024-05-03","cited_by_count":67,"area":"mllm"},{"id":"2309.05950","title":"Language Models as Black-Box Optimizers for Vision-Language Models","created":"2023-09-12","cited_by_count":36,"area":"mllm"},{"id":"2406.01837","title":"Boosting Vision-Language Models with Transduction","created":"2024-06-03","cited_by_count":36,"area":"mllm"},{"id":"2410.19294","title":"Enhancing Zero-Shot Vision Models by Label-Free Prompt Distribution Learning and Bias Correcting","created":"2024-10-25","cited_by_count":26,"area":"mllm"},{"id":"2501.11175","title":"ProKeR: A Kernel Perspective on Few-Shot Adaptation of Large Vision-Language Models","created":"2025-01-19","cited_by_count":15,"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":"2410.15397","title":"IPO: Interpretable Prompt Optimization for Vision-Language Models","created":"2024-10-20","cited_by_count":14,"area":"mllm"},{"id":"2501.03729","title":"Realistic Test-Time Adaptation of Vision-Language Models","created":"2025-01-07","cited_by_count":14,"area":"mllm"},{"id":"2502.19844","title":"ProAPO: Progressively Automatic Prompt Optimization for Visual Classification","created":"2025-02-27","cited_by_count":13,"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":"2506.23856","title":"A Closer Look at Conditional Prompt Tuning for Vision-Language Models","created":"2025-06-30","cited_by_count":8,"area":"mllm"},{"id":"2407.12315","title":"ModalChorus: Visual Probing and Alignment of Multi-modal Embeddings via Modal Fusion Map","created":"2024-07-17","cited_by_count":7,"area":"mllm"},{"id":"2501.04352","title":"Online Gaussian Test-Time Adaptation of Vision-Language Models","created":"2025-01-08","cited_by_count":7,"area":"mllm"},{"id":"2506.17500","title":"Few-Shot, Now for Real: Medical VLMs Adaptation without Balanced Sets or Validation","created":"2025-06-20","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":"2409.11919","title":"LLM-wrapper: Black-Box Semantic-Aware Adaptation of Vision-Language Models for Referring Expression Comprehension","created":"2024-09-18","cited_by_count":3,"area":"mllm"},{"id":"2510.09473","title":"D-TPT: Dimensional Entropy Maximization for Calibrating Test-Time Prompt Tuning in Vision-Language Models","created":"2025-10-10","cited_by_count":3,"area":"mllm"},{"id":"2509.03803","title":"Causality-guided Prompt Learning for Vision-language Models via Visual Granulation","created":"2025-09-04","cited_by_count":2,"area":"mllm"},{"id":"2307.05591","title":"Linear Alignment of Vision-language Models for Image Captioning","created":"2023-07-10","cited_by_count":0,"area":"mllm"},{"id":"2603.02557","title":"CAPT: Confusion-Aware Prompt Tuning for Reducing Vision-Language Misalignment","created":"2026-03-03","cited_by_count":0,"area":"mllm"},{"id":"2606.04385","title":"Geometry-Preserving Unsupervised Alignment for Heterogeneous Foundation Models","created":"2026-06-03","cited_by_count":0,"area":"mllm"},{"id":"2606.22999","title":"Black-Box Continual Learning for Vision-Language Models","created":"2026-06-22","cited_by_count":0,"area":"mllm"}],"next_cursor":null}