{"total":41,"rows":[{"id":"2405.18541","title":"Low-Rank Few-Shot Adaptation of Vision-Language Models","created":"2024-05-28","cited_by_count":104,"area":"mllm"},{"id":"2311.16194","title":"BadCLIP: Trigger-Aware Prompt Learning for Backdoor Attacks on CLIP","created":"2023-11-26","cited_by_count":67,"area":"mllm"},{"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":"2311.16494","title":"ArGue: Attribute-Guided Prompt Tuning for Vision-Language Models","created":"2023-11-27","cited_by_count":39,"area":"mllm"},{"id":"2406.01837","title":"Boosting Vision-Language Models with Transduction","created":"2024-06-03","cited_by_count":36,"area":"mllm"},{"id":"2407.21794","title":"Generalized Out-of-Distribution Detection and Beyond in Vision Language Model Era: A Survey","created":"2024-07-31","cited_by_count":36,"area":"mllm"},{"id":"2407.04603","title":"AWT: Transferring Vision-Language Models via Augmentation, Weighting, and Transportation","created":"2024-07-05","cited_by_count":28,"area":"mllm"},{"id":"2403.09410","title":"XCoOp: Explainable Prompt Learning for Computer-Aided Diagnosis via Concept-guided Context Optimization","created":"2024-03-14","cited_by_count":20,"area":"mllm"},{"id":"2407.03056","title":"Improving Zero-shot Generalization of Learned Prompts via Unsupervised Knowledge Distillation","created":"2024-07-03","cited_by_count":18,"area":"mllm"},{"id":"2310.06123","title":"Text-driven Prompt Generation for Vision-Language Models in Federated Learning","created":"2023-10-09","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":"2412.04378","title":"VladVA: Discriminative Fine-tuning of LVLMs","created":"2024-12-05","cited_by_count":15,"area":"mllm"},{"id":"2505.05180","title":"OpenworldAUC: Towards Unified Evaluation and Optimization for Open-world Prompt Tuning","created":"2025-05-08","cited_by_count":12,"area":"mllm"},{"id":"2408.05775","title":"Efficient Test-Time Prompt Tuning for Vision-Language Models","created":"2024-08-11","cited_by_count":10,"area":"mllm"},{"id":"2505.15130","title":"Few-Shot Adversarial Low-Rank Fine-Tuning of Vision-Language Models","created":"2025-05-21","cited_by_count":9,"area":"mllm"},{"id":"2410.11201","title":"Tree of Attributes Prompt Learning for Vision-Language Models","created":"2024-10-15","cited_by_count":7,"area":"mllm"},{"id":"2502.15809","title":"Black Sheep in the Herd: Playing with Spuriously Correlated Attributes for Vision-Language Recognition","created":"2025-02-19","cited_by_count":7,"area":"mllm"},{"id":"2407.10704","title":"Quantized Prompt for Efficient Generalization of Vision-Language Models","created":"2024-07-15","cited_by_count":6,"area":"mllm"},{"id":"2312.10813","title":"Towards Efficient Vision-Language Tuning: More Information Density, More Generalizability","created":"2023-12-17","cited_by_count":5,"area":"mllm"},{"id":"2411.16018","title":"Style-Pro: Style-Guided Prompt Learning for Generalizable Vision-Language Models","created":"2024-11-25","cited_by_count":5,"area":"mllm"},{"id":"2511.12639","title":"Medical Knowledge Intervention Prompt Tuning for Medical Image Classification","created":"2025-11-16","cited_by_count":5,"area":"mllm"},{"id":"2602.21397","title":"MMLoP: Multi-Modal Low-Rank Prompting for Efficient Vision-Language Adaptation","created":"2026-02-24","cited_by_count":5,"area":"mllm"},{"id":"2308.10061","title":"DPL: Decoupled Prompt Learning for Vision-Language Models","created":"2023-08-19","cited_by_count":4,"area":"mllm"},{"id":"2410.23698","title":"Aggregate-and-Adapt Natural Language Prompts for Downstream Generalization of CLIP","created":"2024-10-31","cited_by_count":4,"area":"mllm"},{"id":"2506.21017","title":"Multimodal Prompt Alignment for Facial Expression Recognition","created":"2025-06-26","cited_by_count":4,"area":"mllm"},{"id":"2407.04207","title":"Elevating All Zero-Shot Sketch-Based Image Retrieval Through Multimodal Prompt Learning","created":"2024-07-05","cited_by_count":3,"area":"mllm"},{"id":"2502.11969","title":"Learning Generalizable Prompt for CLIP with Class Similarity Knowledge","created":"2025-02-17","cited_by_count":3,"area":"mllm"},{"id":"2511.22664","title":"VaMP: Variational Multi-Modal Prompt Learning for Vision-Language Models","created":"2025-11-27","cited_by_count":3,"area":"mllm"},{"id":"2309.07866","title":"Gradient constrained sharpness-aware prompt learning for vision-language models","created":"2023-09-14","cited_by_count":1,"area":"mllm"},{"id":"2410.10247","title":"LPT: Less-overfitting Prompt Tuning for Vision-Language Model","created":"2024-10-14","cited_by_count":1,"area":"mllm"},{"id":"2410.11686","title":"A Survey of Low-shot Vision-Language Model Adaptation via Representer Theorem","created":"2024-10-15","cited_by_count":1,"area":"mllm"},{"id":"2412.19087","title":"MoPD: Mixture-of-Prompts Distillation for Vision-Language Models","created":"2024-12-26","cited_by_count":1,"area":"mllm"},{"id":"2503.06993","title":"CAPT: Class-Aware Prompt Tuning for Federated Long-Tailed Learning with Vision-Language Model","created":"2025-03-10","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":"2508.11870","title":"AdaRing: Towards Ultra-Light Vision-Language Adaptation via Cross-Layer Tensor Ring Decomposition","created":"2025-08-16","cited_by_count":0,"area":"mllm"},{"id":"2508.12399","title":"Federated Cross-Modal Style-Aware Prompt Generation","created":"2025-08-17","cited_by_count":0,"area":"mllm"},{"id":"2603.16653","title":"HeBA: Heterogeneous Bottleneck Adapters for Robust Vision-Language Models","created":"2026-03-17","cited_by_count":0,"area":"mllm"},{"id":"2605.17577","title":"TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models","created":"2026-05-17","cited_by_count":0,"area":"mllm"},{"id":"2608.24142","title":"What Does Prompt Learning Change? -A Natural-Language Concept Analysis of Vision-Language Models","created":"2026-08-25","cited_by_count":0,"area":"mllm"},{"id":"2609.09462","title":"Low-Rank Prompt Learning for Vision-Language Models with Fixed-Token Bases","created":"2026-09-08","cited_by_count":0,"area":"mllm"},{"id":"2610.16666","title":"Revisiting Natural Language Prompts from Large Language Models for Open-Vocabulary Video Recognition","created":"2026-10-12","cited_by_count":0,"area":"mllm"}],"next_cursor":null}