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,
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2verdicts
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FlowCLIP pretrains a traffic encoder via CLIP-style contrastive loss on domain names from side-channel features, then freezes it for linear probing classification that outperforms baselines on later weeks of QUIC traffic.
citing papers explorer
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PCCL: Process Group-Aware Scalable and Generic Collective Algorithm Synthesizer
PCCL synthesizes near-optimal topology-aware collective algorithms for arbitrary patterns while being process group-aware and scalable to subsets of devices.
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FlowCLIP: Contrastive Pretraining Using Domain Names for Encrypted Traffic Classification
FlowCLIP pretrains a traffic encoder via CLIP-style contrastive loss on domain names from side-channel features, then freezes it for linear probing classification that outperforms baselines on later weeks of QUIC traffic.