CoLLM unifies FL PEFT and inference on shared edge replicas via intra-replica model sharing and two-timescale inter-replica coordination, achieving up to 3x higher goodput than prior LLM systems.
Federated fine-tuning for pre-trained foundation models over wireless networks
2 Pith papers cite this work, alongside 4 external citations. Polarity classification is still indexing.
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2026 2verdicts
UNVERDICTED 2representative citing papers
This survey defines the Federated Continual Learning problem, proposes a taxonomy for approaches, reviews applications and metrics, and identifies open challenges in lifelong privacy-preserving learning on non-stationary distributed data.
citing papers explorer
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CoLLM: Continuous Adaptation for SLO-Aware LLM Serving on Shared GPU Clusters
CoLLM unifies FL PEFT and inference on shared edge replicas via intra-replica model sharing and two-timescale inter-replica coordination, achieving up to 3x higher goodput than prior LLM systems.
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Federated continual learning: A comprehensive survey on lifelong and privacy-preserving learning over distributed and non-stationary data
This survey defines the Federated Continual Learning problem, proposes a taxonomy for approaches, reviews applications and metrics, and identifies open challenges in lifelong privacy-preserving learning on non-stationary distributed data.