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cs.LG2026
Adapter-Augmented Bandits for Online Multi-Constrained Multi-Modal Inference Scheduling
Xianzhi Zhang, Yue Xu, Yinlin Zhu +4
Multi-modal large language model (MLLM) inference scheduling enables strong response quality under practical and heterogeneous budgets, beyond what a homogeneous single-backend set…
cs.LG2026
Federated Learning at the Forefront of Fairness: A Multifaceted Perspective
Noorain Mukhtiar, Adnan Mahmood, Yipeng Zhou +3
Fairness in Federated Learning (FL) is emerging as a critical factor driven by heterogeneous clients' constraints and balanced model performance across various scenarios. In this s…