PCCL synthesizes near-optimal topology-aware collective algorithms for arbitrary patterns while being process group-aware and scalable to subsets of devices.
The Sweet Danger of Sugar: Debunking Representation Learning for Encrypted Traffic Classification,
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FlowCLIP applies contrastive pretraining with domain-name text supervision to learn transferable representations from QUIC traffic side-channel features, matching supervised performance on time-split evaluation.
citing papers explorer
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FlowCLIP: Contrastive Pretraining Using Domain Names for Encrypted Traffic Classification
FlowCLIP applies contrastive pretraining with domain-name text supervision to learn transferable representations from QUIC traffic side-channel features, matching supervised performance on time-split evaluation.