{"total":21,"rows":[{"id":"2406.03150","title":"Sample-specific Masks for Visual Reprogramming-based Prompting","created":"2024-06-05","cited_by_count":18,"area":null},{"id":"2502.00896","title":"LoR-VP: Low-Rank Visual Prompting for Efficient Vision Model Adaptation","created":"2025-02-02","cited_by_count":17,"area":null},{"id":"2404.00095","title":"GDA: Generalized Diffusion for Robust Test-time Adaptation","created":"2024-03-29","cited_by_count":14,"area":null},{"id":"2410.24018","title":"Bayesian-guided Label Mapping for Visual Reprogramming","created":"2024-10-31","cited_by_count":12,"area":null},{"id":"2402.10380","title":"Subgraph-level Universal Prompt Tuning","created":"2024-02-16","cited_by_count":9,"area":null},{"id":"2506.01000","title":"Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts","created":"2025-06-01","cited_by_count":4,"area":null},{"id":"2506.04650","title":"Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction","created":"2025-06-05","cited_by_count":4,"area":null},{"id":"2407.17491","title":"Robust Adaptation of Foundation Models with Black-Box Visual Prompting","created":"2024-07-04","cited_by_count":3,"area":null},{"id":"2505.02406","title":"Token Coordinated Prompt Attention is Needed for Visual Prompting","created":"2025-05-05","cited_by_count":3,"area":null},{"id":"2409.16491","title":"Proactive Schemes: A Survey of Adversarial Attacks for Social Good","created":"2024-09-24","cited_by_count":2,"area":null},{"id":"2506.00620","title":"Model Reprogramming Demystified: A Neural Tangent Kernel Perspective","created":"2025-05-31","cited_by_count":2,"area":null},{"id":"2510.12160","title":"State Space Prompting via Gathering and Spreading Spatio-Temporal Information for Video Understanding","created":"2025-10-14","cited_by_count":2,"area":null},{"id":"2408.07944","title":"Training Spatial-Frequency Visual Prompts and Probabilistic Clusters for Accurate Black-Box Transfer Learning","created":"2024-08-15","cited_by_count":1,"area":null},{"id":"2412.16956","title":"Semantic Hierarchical Prompt Tuning for Parameter-Efficient Fine-Tuning","created":"2024-12-22","cited_by_count":1,"area":null},{"id":"2504.18158","title":"E-InMeMo: Enhanced Prompting for Visual In-Context Learning","created":"2025-04-25","cited_by_count":1,"area":null},{"id":"2510.19487","title":"Towards Single-Source Domain Generalized Object Detection via Causal Visual Prompts","created":"2025-10-22","cited_by_count":1,"area":null},{"id":"2509.03494","title":"Parameter-Efficient Adaptation of mPLUG-Owl2 via Pixel-Level Visual Prompts for NR-IQA","created":"2025-09-03","cited_by_count":0,"area":null},{"id":"2510.07823","title":"Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation","created":"2025-10-09","cited_by_count":0,"area":null},{"id":"2606.01945","title":"Beyond Low-Rank: Low-Rank Sparse Prompting via Spiking Neural Network and Prompt Factorization","created":"2026-06-01","cited_by_count":0,"area":null},{"id":"2608.21194","title":"ES-VP : Energy-Shaped Dynamic Visual Prompting for Efficient Model Adaptation","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2609.36661","title":"You Only Reprogram Once: Rethinking Prolonged Training for Visual Reprogramming","created":"2026-09-29","cited_by_count":0,"area":null}],"next_cursor":null}