3 papers
cs.CV2026
Federated Balanced Learning
Jiaze Li, Haoran Xu, Wanyi Wu +9
Federated learning is a paradigm of joint learning in which clients collaborate by sharing model parameters instead of data. However, in the non-iid setting, the global model exper…
cs.CV2026
Federated Joint Learning for Domain and Class Generalization
Haoran Xu, Jiaze Li, Jianzhong Ju +1
Efficient fine-tuning of visual-language models like CLIP has become crucial due to their large-scale parameter size and extensive pretraining requirements. Existing methods typica…
cs.CV2026
Vision Also You Need: Navigating Out-of-Distribution Detection with Multimodal Large Language Model
Haoran Xu, Yanlin Liu, Zizhao Tong +8
Out-of-Distribution (OOD) detection is a critical task that has garnered significant attention. The emergence of CLIP has spurred extensive research into zero-shot OOD detection, o…