{"total":22,"rows":[{"id":"2405.09771","title":"Harmonizing Generalization and Personalization in Federated Prompt Learning","created":"2024-05-16","cited_by_count":27,"area":"mllm"},{"id":"2409.19610","title":"Federated Learning from Vision-Language Foundation Models: Theoretical Analysis and Method","created":"2024-09-29","cited_by_count":22,"area":"mllm"},{"id":"2410.10114","title":"Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models","created":"2024-10-14","cited_by_count":17,"area":"mllm"},{"id":"2501.02461","title":"FedRSClip: Federated Learning for Remote Sensing Scene Classification Using Vision-Language Models","created":"2025-01-05","cited_by_count":11,"area":"mllm"},{"id":"2411.14717","title":"FedMLLM: Federated Fine-tuning MLLM on Multimodal Heterogeneity Data","created":"2024-11-22","cited_by_count":7,"area":"mllm"},{"id":"2506.09638","title":"FedVLMBench: Benchmarking Federated Fine-Tuning of Vision-Language Models","created":"2025-06-11","cited_by_count":6,"area":"mllm"},{"id":"2404.11046","title":"Lightweight Unsupervised Federated Learning with Pretrained Vision Language Model","created":"2024-04-17","cited_by_count":5,"area":"mllm"},{"id":"2501.13904","title":"Privacy-Preserving Personalized Federated Prompt Learning for Multimodal Large Language Models","created":"2025-01-23","cited_by_count":5,"area":"mllm"},{"id":"2503.05776","title":"FAA-CLIP: Federated Adversarial Adaptation of CLIP","created":"2025-02-26","cited_by_count":5,"area":"mllm"},{"id":"2507.05394","title":"pFedMMA: Personalized Federated Fine-Tuning with Multi-Modal Adapter for Vision-Language Models","created":"2025-07-07","cited_by_count":4,"area":"mllm"},{"id":"2409.06067","title":"MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning","created":"2024-09-09","cited_by_count":3,"area":"mllm"},{"id":"2505.23024","title":"An Empirical Study of Federated Prompt Learning for Vision Language Model","created":"2025-05-29","cited_by_count":3,"area":"mllm"},{"id":"2310.03103","title":"Learning to Prompt Your Domain for Vision-Language Models","created":"2023-10-04","cited_by_count":2,"area":"mllm"},{"id":"2506.16218","title":"FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models","created":"2025-06-19","cited_by_count":2,"area":"mllm"},{"id":"2511.16423","title":"TOFA: Training-Free One-Shot Federated Adaptation for Vision-Language Models","created":"2025-11-20","cited_by_count":1,"area":"mllm"},{"id":"2603.26786","title":"A Step Toward Federated Pretraining of Multimodal Large Language Models","created":"2026-03-25","cited_by_count":1,"area":"mllm"},{"id":"2503.22263","title":"FLIP: Towards Comprehensive and Reliable Evaluation of Federated Prompt Learning","created":"2025-03-28","cited_by_count":0,"area":"mllm"},{"id":"2505.01851","title":"Mitigating Group-Level Fairness Disparities in Federated Visual Language Models","created":"2025-05-03","cited_by_count":0,"area":"mllm"},{"id":"2512.04305","title":"How (Mis)calibrated is your Federated CLIP and what to do about it?","created":"2025-12-03","cited_by_count":0,"area":"mllm"},{"id":"2607.12112","title":"Continual Learning with Elastic Regularization and Synthetic Replay for Federated MLLM Fine-Tuning","created":"2026-07-13","cited_by_count":0,"area":"mllm"},{"id":"2609.22162","title":"Beyond Raw Context Transfer: Representation-based Federated Retrieval-Augmented Generation","created":"2026-08-26","cited_by_count":0,"area":"mllm"},{"id":"2610.01625","title":"Beyond Domain-Level Adaptation: Margin-Oriented Semantic-Appearance Interaction Correction for Personalized Federated Vision-Language Models","created":"2026-10-01","cited_by_count":0,"area":"mllm"}],"next_cursor":null}