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cs.AI2026
ProgRouter: Online Progress-Guided Orchestration for Multi-Agent LLM Workflows under Quality-Cost Tradeoffs
Songyuan Li, Ahmed M. Abdelmoniem, Shiqiang Wang
Multi-agent large language model (LLM) workflows have emerged as a powerful paradigm for solving complex, open-ended tasks through collaborative reasoning among specialized LLM age…
cs.LG2026
HASA: Subnet Allocation for Compute-Constrained Model-Heterogeneous Federated Learning
Amir Hossein Shahdadian, Ahmed M. Abdelmoniem, Mahdi Taheri +2
Edge services increasingly use federated learning to personalize on-device models while keeping sensitive data local. In practice, deployments must handle heterogeneity in both cli…
cs.LG2026
BLOSSOM: Block-wise Federated Learning Over Shared and Sparse Observed Modalities
Pranav M R, Jayant Chandwani, Ahmed M. Abdelmoniem +1
Multimodal federated learning (FL) is essential for real-world applications such as autonomous systems and healthcare, where data is distributed across heterogeneous clients with v…