DualKV eliminates redundant prompt replication in RL training attention kernels via fused dual-KV CUDA operations and token repacking, delivering 1.63-3.82x policy-update speedups while remaining mathematically equivalent to standard attention.
Flash A ttention-3: Fast and accurate attention with asynchrony and low-precision
2 Pith papers cite this work. Polarity classification is still indexing.
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2026 2representative citing papers
Focus learns a few centroids to gate long-range token attention, producing sparse attention that matches or beats full attention quality with up to 8.6x speedup at million-token lengths.
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DualKV: Shared-Prompt Flash Attention for Efficient RL Training with Large Rollouts and Long Contexts
DualKV eliminates redundant prompt replication in RL training attention kernels via fused dual-KV CUDA operations and token repacking, delivering 1.63-3.82x policy-update speedups while remaining mathematically equivalent to standard attention.