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cs.CV2026
Understanding Adversarial Transferability in Vision-Language Models for Autonomous Driving: A Cross-Architecture Analysis
David Fernandez, Pedram MohajerAnsari, Amir Salarpour +1
Vision-language models (VLMs) are increasingly used in autonomous driving because they combine visual perception with language-based reasoning, supporting more interpretable decisi…
cs.CV2025
FedVLM: Scalable Personalized Vision-Language Models through Federated Learning
Arkajyoti Mitra, Afia Anjum, Paul Agbaje +2
Vision-language models (VLMs) demonstrate impressive zero-shot and few-shot learning capabilities, making them essential for several downstream tasks. However, fine-tuning these mo…