Cooperative MARL is commonly evaluated through cooperation discovery from random initialization, leaving open whether continued optimization can destabilize learned cooperation. Actor-critic comparisons can also conflate critic presence with value gradients entering shared actor representations. We study cooperation ma...
Chao-Yuan Hao, Wen-Tao Yue, Tian-You Lai et al.· 0 citations
Federated parameter-efficient fine-tuning enables distributed clients to adapt pretrained vision-language models without sharing raw data or updating the full backbone. Its effectiveness, however, is limited by domain heterogeneity across clients. Existing personalized methods separate globally shared knowledge from cl...
Wen-Tao Yue, Qing-Yu Mao, Tian-You Lai et al.· 0 citations
Federated learning (FL) on heterogeneous edge devices must jointly accommodate unequal resource budgets and domain-shifted local data. Existing resource-adaptive methods decide how much of a model each client trains but not where retained capacity should reside or how it should be shared, whereas federated domain-gener...
Wen-Tao Yue, Tian-You Lai, Hong-Jiao Li et al.· 0 citations
Breast ultrasound diagnosis relies on clinically meaningful semantic concepts, yet most deep learning methods adopt end-to-end image-to-label paradigms that lack interpretability and robustness. While concept-based approaches offer a promising alternative, they often assume complete annotations or require multimodal in...
Wen-Tao Yue, Tian-You Lai, Jia-Yu Luo et al.· 0 citations
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